Visual Inspection Research Articles

Acute response to resistance exercise and later development of arm lymphedema in breast cancer survivors: An exploratory follow-up of a randomized cross-over trial

BackgroundIn breast cancer survivors at risk for lymphedema, variation in lymphatic function and arm volume has been observed related to a bout of exercise, with potential for prediction of breast cancer-related arm lymphedema (BCRaL). This novel, exploratory study examined the acute lymphatic response to resistance exercise and later development of BCRaL in women at high risk for BCRaL. MethodsOne year after participation in a cross-over trial evaluating the acute lymphatic response to upper-extremity resistance exercise (low-and heavy-load), participants were assessed for BCRaL (n ​= ​16). The response to exercise was assessed before and after (post, 24- and 72-hrs) each exercise bout as extracellular fluid (L-Dex; bioimpedance spectroscopy (BIS)), interarm volume % difference (IVD; Dual-energy x-ray absorptiometry (DXA)) and symptoms (Numeric rating scale, 0–10 (NRS)). BCRaL at follow-up was defined as presence of one objective indicator (L-Dex >10, change ≥+6.5, IVD >5%) plus one objective or subjective indicator (interarm symptom ≥1 or visual inspection). Descriptive statistics were used to compare the acute response between participants with and without BCRaL at follow-up. ResultsNo trends indicating a similar acute response to exercise was observed in participants who later developed BCRaL (n ​= ​5). There were no observable differences in acute lymphatic response between participants that developed BCRaL and those who did not, both at an individual and group level. ConclusionsFindings from this exploratory study showed no evidence to suggest that the acute response to resistance exercise can predict BCRaL development.

Innovative magnetic flux leakage applications in non destructive testing of metallic ropes

The Magnetic Flux Leakage (MFL) principle applied to metallic ropes, also called Magneto-inductive (MI), is not a new non destructive testing (NDT) technique and has been applied from several tens of years in ropeway plants according standards as or CEI EN 12927. The recent evolution of international standards, regarding the discard criteria of metallic ropes in other sectors, as in ISO4309, start to introduce the MFL beside visual inspection in lifting applications. Even if the component under control is always one or more ropes, the discard criteria, the rope conformation and the fault typologies can be influenced by the application sector. Different magnetic detectors have been developed by the Authors in order to satisfy the several technical constraints and practical requirements of the different field of applications. Several new application in industrial and civil sector as hoisting and elevators are starting to use this kind of non destructive methodology and new sensor with peculiar characteristics have been developed and implemented. In this paper recent development on magnetic flux leakage applied on metallic ropes is then presented. Different theoretical and practical experiences in the magnetic design, material characterization of metallic ropes and in the signal filtering system is presented and discussed.

Real-Time Phased Array Ultrasonic Monitoring of Debonding Growth Under Cycling Loading in CFRP

Carbon Fibre Reinforced Polymer (CFRP) composites are widely employed in diverse industries due to their specific stiffness and strength, and corrosion resistance. However, over time, service-induced damage can initiate a failure that can threaten the operation’s safety and reliability, especially in critical industries like aerospace applications. The challenge lies in identifying and monitoring the defects before they escalate into serious issues. Non-Destructive Testing (NDT) methods play a pivotal role in this scenario, aiming to detect and evaluate defects without causing harm to the material. Detecting flaws in composite materials such as CFRP remains a complex task. Traditional NDT methods often struggle to effectively pinpoint and assess defects within these intricate structures. However, recent advancements in ultrasonic testing, especially Phased Array Ultrasonic Testing (PAUT), show promise in examining the internal composition of CFRP composites with higher accuracy and reliability. This study aims to demonstrate the applicability of PAUT for real-time monitoring of debond growth under dynamic loading. The loading was applied to the test specimens up to one million cycles, and 64 elements 2 MHz linear phased array probe was attached to the specimen. The acquired signals were analyzed and could also be recorded for offline processing or archiving. To validate the credibility of the findings, the performance of PAUT was compared to Acoustic Emission (AE), a well-established method for detecting and analysing high-frequency signals emitted by materials undergoing deformation or damage. Encouragingly, both methods exhibited similar trends in capturing the growth of debond. Furthermore, to verify the final defect lengths, post-test ultrasonic C-Scans utilizing the through transmission technique were conducted, complemented by visual inspections. These assessments served to confirm the accuracy and reliability of the results obtained through Phased Array Ultrasonic Testing. Real-time monitoring of composite structures using phased array technology comprises a valuable tool for real- time assessment of debonding in the composite. As industries continue to rely on Carbon Fibre Reinforced Polymer composites for multifaceted applications, the utilization of advanced Non-Destructive Testing methodologies like Phased Array Ultrasonic Testing emerges as a cornerstone in guaranteeing their continued integrity and performance.

An innovative microplastic extraction technique: the switchable calcium chloride density separation column tested for biodegradable polymers, polyethylene, and polyamide

Extracting microplastics from complex matrices poses challenges due to the potential impact of harsh chemical treatments on microplastic properties. For fate and hazard assessment reliable techniques are needed to not only quantify the particle number but also to assess the physicochemical properties of environmental microplastics with minimum changes induced by extraction. Here we present the method development for an innovative and non-destructive extraction protocol based on a switchable calcium chloride density separation column. In contrast to commonly reported extraction protocols, the presented technique is suitable for targeted microplastic property analysis (e.g., surface chemistry and texture) by keeping chemical treatments (such as oxidation and enzymatic digestion) to a minimum. By adjusting the temperature we can control the aggregate state of the highly concentrated salt solution, allowing to separate the microplastics from matrix by cutting of purified, solidified samples. Harsh chemical treatments are avoided, as well as obstruction of microplastic extraction by adsorption to matrix components when passing the tap at the bottom of traditional density separation funnels.The use of microplastics that were prelabeled with a fluorescence dye helped to solve difficulties observed during method development by visual inspection before measurement of extraction efficiency: We spiked a blank compost with low-density polyethylene (LDPE) and polyamide (PA). Additionally, UV aged LDPE was used to demonstrate applicability to more hydrophilic, more environmentally relevant microplastics. The obtained initial results show high recovery of both unaged and aged LDPE over 97 wt.-% and an efficient compost removal but a lower and less robust recovery (between 68 and 18 wt.-%) for PA particles that are more challenging to extract due to an unfortunate synergistic combination of smaller particle size and higher density. Method adaptation to other microplastic types may still be necessary. In short:A low-cost and simple approach without oxidation to extract (pre-aged) microplastics from compostMethod development by visual observation using fluorescent labelled microplastics and method validation by spike-recovery tests

Handheld echocardiography for the screening and diagnosis of rheumatic heart disease: a systematic review to inform WHO guidelines

Early detection and diagnosis of acute rheumatic fever and rheumatic heart disease are key to preventing progression, and echocardiography has an important diagnostic role. Standard echocardiography might not be feasible in high-prevalence regions due to its high cost, complexity, and time requirement. Handheld echocardiography might be an easy-to-use, low-cost alternative, but its performance in screening for and diagnosing acute rheumatic fever and rheumatic heart disease needs further investigation. In this systematic review and meta-analysis, we searched Embase, MEDLINE, LILACS, and Conference Proceedings Citation Index-Science up to Feb 9, 2024, for studies on the screening and diagnosis of acute rheumatic fever and rheumatic heart disease using handheld echocardiography (index test) or standard echocardiography or auscultation (reference tests) in high-prevalence areas. We included all studies with useable data in which the diagnostic performance of the index test was assessed against a reference test. Data on test accuracy in diagnosing rheumatic heart disease, acute rheumatic fever, or carditis with acute rheumatic fever (primary outcomes) were extracted from published articles or calculated, with authors contacted as necessary. Quality of evidence was appraised using GRADE and QUADAS-2 criteria. We summarised diagnostic accuracy statistics (including sensitivity and specificity) and estimated 95% CIs using a bivariate random-effects model (or univariate random-effects models for analyses including three or fewer studies). Area under the curve (AUC) was calculated from summary receiver operating characteristic curves. Heterogeneity was assessed by visual inspection of plots. This study was registered with PROSPERO (CRD42022344081). Out of 4868 records we identified 11 studies, and two additional reports, comprising 15 578 unique participants. Pooled data showed that handheld echocardiography had high sensitivity (0·87 [95% CI 0·76-0·93]), specificity (0·98 [0·71-1·00]), and overall high accuracy (AUC 0·94 [0·84-1·00]) for diagnosing rheumatic heart disease when compared with standard echocardiography (two studies; moderate certainty of evidence), with better performance for diagnosing definite compared with borderline rheumatic heart disease. High sensitivity (0·79 [0·73-0·84]), specificity (0·85 [0·80-0·89]), and overall accuracy (AUC 0·90 [0·85-0·94]) for screening rheumatic heart disease was observed when pooling data of handheld echocardiography versus standard echocardiography (seven studies; high certainty of evidence). Most studies had a low risk of bias overall. Some heterogeneity was observed for sensitivity and specificity across studies, possibly driven by differences in the prevalence and severity of rheumatic heart disease, and level of training or expertise of non-expert operators. Handheld echocardiography has a high accuracy and diagnostic performance when compared with standard echocardiography for diagnosing and screening of rheumatic heart disease in high-prevalence areas. World Health Organization. For the Chinese, French, Italian, Persian, Portuguese, Spanish and Urdu translations of the abstract see Supplementary Materials section.

Non-contact Testing of Large Concrete Structures for Voids and Delaminations

Concrete is the most used construction material for civil engineering structures, as it is reliable, cost-efficient, and long lasting. Infrastructure made of reinforced concrete can be used for many decades, provided that maintenance is rigorous. The necessary periodic checks are typically manual tasks, including visual inspection for defects on the outside and hammering to find internal voids and imminent spalling. In this a paper, a non-contact system for automated inspection is presented. Two parallel lasers are used with a scanning head on a mobile platform to cover large areas. The first laser emits a high energy pulse, igniting plasma on the surface and subsequently inducing a shock wave into the structure. The second laser measures the resulting vibration. Signal analysis of individual measurement points give a first indication about the presence of faults. Unsupervised learning and visual computing are used to find and narrow down damaged areas in the scanning data with higher probability. After systematic testing in the laboratory, measurements were conducted recently in two tunnels with concrete linings. This paper provides an overview of the developed hardware and signal analysis techniques. Furthermore, the recent verification results are presented for the first time. In future, the proposed method can be combined with geometric scans and automated optical inspection of the surface to offer a holistic inspection approach and relieve the authorities that are responsible for operation and maintenance of the growing number of aging infrastructures.

Better Understanding Differences in Attribution Methods via Systematic Evaluations.

Deep neural networks are very successful on many vision tasks, but hard to interpret due to their black box nature. To overcome this, various post-hoc attribution methods have been proposed to identify image regions most influential to the models' decisions. Evaluating such methods is challenging since no ground truth attributions exist. We thus propose three novel evaluation schemes to more reliably measure the faithfulness of those methods, to make comparisons between them more fair, and to make visual inspection more systematic. To address faithfulness, we propose a novel evaluation setting (DiFull) in which we carefully control which parts of the input can influence the output in order to distinguish possible from impossible attributions. To address fairness, we note that different methods are applied at different layers, which skews any comparison, and so evaluate all methods on the same layers (ML-Att) and discuss how this impacts their performance on quantitative metrics. For more systematic visualizations, we propose a scheme (AggAtt) to qualitatively evaluate the methods on complete datasets. We use these evaluation schemes to study strengths and shortcomings of some widely used attribution methods over a wide range of models. Finally, we propose a post-processing smoothing step that significantly improves the performance of some attribution methods, and discuss its applicability.

Analysis of the structural behavior of reinforced concrete components with acoustic emission analysis

The use of non-destructive testing methods can provide insights into processes within the interiors of structures. Acoustic emission testing is one of the non-destructive testing methods that allows the detection of material damage during its occurrence. When structures, such as concrete components, fail under load, elastic waves are generated, propagating within the component. These signals can be detected by acoustic emission sensors placed on the surface of the component, enabling the tracking of the material's condition and the location of failure. This paper summarizes recent applications of acoustic emission measurements on large-scale laboratory specimens made of reinforced concrete. The first example describes measurements during a tensile fatigue test on a large- scale reinforced concrete specimen to investigate the fatigue behaviour of an embedded concrete dowel. The second example involves measurements during a dynamic three-point bending test to examine the fatigue behaviour of a prestressed concrete railway sleeper. The third example describes a full-scale test conducted on a flat slab concrete test specimen with dimensions of 2.8 m × 2.8 m. The objective of these investigations is the development and optimization of new components to enhance punching shear resistance and provide an economical solution. To detect microcracking during loading acoustic emission measurement has been carried out using broadband sensors with a measurement frequency of up to 200 kHz which were especially developed for the detection of microcracks in concrete. For the three-dimensional location of the acoustic emission events, 16 of these acoustic emission sensors were attached to the surface of the specimens. Most of the events were in the centre of the sample in the punching area. These events form a circular structure with a diameter of approximately 1m. A visual inspection of the sample after the experiment shows that macroscopic cracks have formed in this area, which extend up to the surface of the sample.

Recent research and developments of degradation assessment and its diagnosis methods for solar PV plant: a review

The world is moving forward to a transition in the form of increasing the contribution of renewable energy sources in the energy sector, and among these, solar photovoltaic-based power generation is catching pace. Several factors are responsible for the lowering of outputs due to different degradation causes such as hotspots, corrosion, humidity, ultraviolet (UV) irradiation, temperature effects, dust, aging, weathering, yellowing, snail trails, discoloration, junction box failure, delamination, cracks, and faults from the solar photovoltaic (PV) plants. This paper presents a comprehensive review of the various form of degradation and their implications on solar PV power plant performance. The review has been carried out considering the different degradation causes and their identification methods in solar PV plant. Further, the analysis has been done on the basis of the earlier studies to understand the rates of degradation for various solar PV power plants in various climatic conditions. The PV technologies used in solar power plants are also responsible for the change in the performance of power plants over time; therefore, degradation based on different solar PV cell technologies is also analyzed. The visual inspection tools like thermal imaging with IR cameras help identify areas with abnormal heat patterns, indicating potential issues like cell or interconnect failures, loose electrical connections, or bypass diode malfunctions while EL cameras are used to identify low-level electrical excitation and defects such as cracks, hotspots, and cell-level degradation.

Plant Disease Detection

Abstract: This project addresses the critical challenge of plant disease detection in India, a nation where agriculture supports nearly 70% of the population. Traditional procedures for identifying plant diseases are both labor-intensive and time-consuming. To enhance efficiency and accuracy, this project introduces an innovative approach that integrates machine learning and image processing techniques. By analyzing images of leaves, the system identifies diseases based on key factors such as leaf color, damage extent, area, and texture parameters. Unlike conventional methods that depend on visual inspections or chemical processes, this automated system provides a cost-effective and efficient solution for monitoring extensive crop fields. By leveraging statistical machine learning and advanced image processing algorithms, the proposed solution ensures precise disease detection with minimized computational complexity and reduced prediction time

Dental Carries Prediction and Prevention

Abstract: A large percentage of people worldwide suffer from dental cavities, which are prevalent disorders. They caused by bacterial activity, can lead to permanent damage to teeth. They pose a risk to tooth health without timely intervention. In order to stop additional harm, early identification and treatment are essential. Traditionally, x-rays or a direct visual inspection are done by dentists to detect cavities. On the other hand, automated systems that employ image processing methods including region recognition, binary image synthesis, and RGB to Gray conversion can help locate cavities in x-ray pictures. Automated tools that utilize ordinary cameras for dental image analysis are also being explored, showing promising results.

Management of intraspecific aggression in two bull giraffes (Giraffa camelopardalis ssp. rothschildi).

Maintaining nonbreeding individuals in zoological collections may sometimes necessitate housing bachelor groups. In turn, intact cohabiting males may express increased intraspecific agonistic behaviors, and management intervention may be indicated. Where castration is deemed inappropriate (e.g., future breeding, or anesthesia and surgery-related risk), the immune contraceptive gonadotrophin-releasing hormone (GnRH) is increasingly used as an alternative. When intraspecific aggression (sparring) in two bull giraffes housed as a bachelor pair at Knowsley Safari, UK, escalated in frequency and intensity (despite management interventions), further mediation was warranted to moderate sparring behaviors. The Ex situ Program recommendation was for one giraffe, the (slightly) older, outwardly mature (darker, strong musth) individual, to be treated with the GnRH vaccine Improvac® (Zoetis). To gauge the efficacy of vaccination, behavioral observations were conducted during each vaccination phase to identify changes in the frequency of sparring behaviors. In addition, fecal samples were collected by keepers and sent to Chester Zoo's Endocrine Diagnostic Laboratory for analysis to compare androgen levels between the pre- and postvaccination phases. Testicular atrophy was investigated using both visual inspection and photographic images. The GnRH vaccine Improvac® initially appeared to be associated with reduced aggressive behaviors in the two bull giraffes. Sparring behaviors decreased in frequency after each vaccination phase, although these did not significantly diminish until phase 4. Physiological markers were inconclusive as testosterone concentrations varied throughout the phases, although levels remained low after the fourth vaccination phase. Approximately 8 months following the initial vaccination with Improvac®, the unvaccinated bull exhibited heightened aggression, resulting in physical aggression and injury to the vaccinated bull. As a result, both bulls are now on an Improvac® vaccination schedule, which has enabled them to remain housed together as a bachelor pair.

Jet-injection assisted photodynamic therapy for superficial and nodular basal cell carcinoma: A pilot study.

Photodynamic therapy (PDT) with topical δ-Aminolevulinic acid (ALA) has efficacy in treating basal cell carcinoma (BCC) but is limited by incomplete penetration of ALA into the deeper dermis. This prospective open-label pilot trial investigated the safety and efficacy of photosensitizer jet injection for PDT (JI-PDT) for BCC treatment. It was performed with 15 patients (n = 15) with histologically confirmed, untreated, low-risk nodular BCCs at a single institution. For the intervention, JI-PDT patients (n = 11) received two sessions of jet-injected ALA with PDT separated by four to 6 weeks. To further understand treatment technique, another group of patients (n = 4) received jet-injected ALA followed by tumor excision and fluorescence microscopy (JI-E). Treatment tolerability was assessed by local skin responses (LSR) score at five distinct time intervals. Fluorescence microscopy assessed protoporphyrin IX penetration depth and biodistribution within the tumor. At the primary endpoint, tumor clearance was evaluated via visual inspection, dermoscopy and reflectance confocal microscopy. Postinjection and postillumination pain levels, and patient satisfaction, were scored on a 0-10 scale. Fifteen participants with mean age of 58.3, who were 15/15 White, non-Hispanic enrolled. The median composite LSR score immediately after JI-PDT was 5(interquartile range [IQR] = 3) which decreased to 0.5 (IQR = 1) at primary endpoint (p < 0.01). Immunofluorescence of excised BCC tumors with jet-injected ALA showed photosensitizer penetration into papillary and reticular dermis. Of the 13 JI-PDT tumors, 11 had tumor clearance confirmed, 1 recurred, and 1 was lost to follow-up. 1/11 patients experienced a serious adverse event of cellulitis. 70% of patients had local scarring at 3 months. Patients reported an average pain level of 5.6 (standard deviation [SD] = 2.3) during jet injection and 3.7 (SD = 1.8) during light illumination. Jet injection of ALA for PDT treatment of nodular low-risk BCC is tolerable and feasible and may represent a novel modality to improve PDT.

Alrecon: computed tomography reconstruction web application based on Solara

Synchrotron X-ray computed tomography is a non-destructive 3D imaging technique that offers the possibility to study the internal microstructure of samples with high spatial and temporal resolution. Given its unmatched image quality and acquisition speed, and the possibility to preserve the specimens, there is an increasing demand for this technique, from scientific users from innumerable disciplines. Computed tomography reconstruction is the computational process by which experimental radiographs are converted to a meaningful 3-dimensional image after the scan. The procedure involves pre-processing steps for image background and artifact correction on raw data, a reconstruction step approximating the inverse Radon-transform, and writing of the reconstructed volume image to disk. Several open-source Python packages exist to help scientists in the process of tomography reconstruction, by offering efficient implementations of reconstruction algorithms exploiting central or graphics processing unit (CPU and GPU, respectively), and by automating significant portions of the data processing pipeline. A further increase in productivity is attained by scheduling and parallelizing demanding reconstructions on high performance computing (HPC) clusters. Nevertheless, visual inspection and interactive selection of optimal reconstruction parameters remain crucial steps that are often performed in close interaction with the end-user of the data. As a result, the reconstruction task involves more than one software. Graphical user interfaces are provided to the user for fast inspection and optimization of reconstructions, while HPC resources are often accessed through scripts and command line interface. We propose Alrecon, a pure Python web application for tomographic reconstruction built using Solara. Alrecon offers users an intuitive and reactive environment for exploring data and customizing reconstruction pipelines. By leveraging upon popular 3D image visualization tools, and by providing a user-friendly interface for reconstruction scheduling on HPC resources, Alrecon guarantees productivity and efficient use of resources for any type of beamline user.

Optimized fertilization using online soil nitrate data

Abstract. A new soil nitrate monitoring system that was installed in a cultivated field enabled us, for the first time, to control the nitrate concentration across the soil profile. The monitoring system was installed in a full-scale agricultural greenhouse setup that was used for growing a bell pepper crop. Continuous measurements of soil nitrate concentrations were performed across the soil profile of two plots: (a) an adjusted fertigation plot, in which the fertigation regime was frequently adjusted according to the dynamic variations in soil nitrate concentration, and (b) a control plot, in which the fertigation was managed according to a predetermined fertigation schedule that is standard practice for the area. The results enabled an hourly resolution in tracking the dynamic soil nitrate concentration variations in response to daily fertigation and crop demand. Nitrate–nitrogen (N–NO3) concentrations in and below the root zone, under the control plot, reached very high levels of ∼ 180 ppm throughout the entire season. Obviously, this concentration reflects excessive fertigation, which is far beyond the plant demand, entailing severe groundwater pollution potential. On the other hand, frequent adjustments of the fertigation regime, which were carried out under the adjusted fertigation plot, enabled control of the soil nitrate concentration around the desired concentration threshold. This enabled a substantial reduction of 38 % in fertilizer application while maintaining maximum crop yield and quality. Throughout this experiment, decision-making on the fertigation adjustments was done manually based on visual inspections of the soil's reactions to changes in the fertigation regime. Nevertheless, it is obvious that an algorithm that continuously processes the soil nitrate concentration across the soil profile and provides direct fertigation commands could act as a “fertistat” that sets the soil nutrients at a desired optimal level. Consequently, it is concluded that fertigation that is based on continuous monitoring of the soil nitrate concentration may ensure nutrient application that accounts for plant demand, improves agricultural profitability, minimizes nitrate down-leaching and significantly reduces water resource pollution.

Efficacy and safety of hyperbaric oxygen therapy for long COVID: a protocol for systematic review and meta-analysis

IntroductionThere is still a lack of therapeutic options for long COVID. Several studies have shown the benefit of hyperbaric oxygen therapy (HBOT) on long COVID. However, the efficacy and safety...

Enhancing Accuracy in Breast Density Assessment Using Deep Learning: A Multicentric, Multi-Reader Study

The evaluation of mammographic breast density, a critical indicator of breast cancer risk, is traditionally performed by radiologists via visual inspection of mammography images, utilizing the Breast Imaging-Reporting and Data System (BI-RADS) breast density categories. However, this method is subject to substantial interobserver variability, leading to inconsistencies and potential inaccuracies in density assessment and subsequent risk estimations. To address this, we present a deep learning-based automatic detection algorithm (DLAD) designed for the automated evaluation of breast density. Our multicentric, multi-reader study leverages a diverse dataset of 122 full-field digital mammography studies (488 images in CC and MLO projections) sourced from three institutions. We invited two experienced radiologists to conduct a retrospective analysis, establishing a ground truth for 72 mammography studies (BI-RADS class A: 18, BI-RADS class B: 43, BI-RADS class C: 7, BI-RADS class D: 4). The efficacy of the DLAD was then compared to the performance of five independent radiologists with varying levels of experience. The DLAD showed robust performance, achieving an accuracy of 0.819 (95% CI: 0.736–0.903), along with an F1 score of 0.798 (0.594–0.905), precision of 0.806 (0.596–0.896), recall of 0.830 (0.650–0.946), and a Cohen’s Kappa (κ) of 0.708 (0.562–0.841). The algorithm achieved robust performance that matches and in four cases exceeds that of individual radiologists. The statistical analysis did not reveal a significant difference in accuracy between DLAD and the radiologists, underscoring the model’s competitive diagnostic alignment with professional radiologist assessments. These results demonstrate that the deep learning-based automatic detection algorithm can enhance the accuracy and consistency of breast density assessments, offering a reliable tool for improving breast cancer screening outcomes.

Transcutaneous bilirubinometry for detecting jaundice in term or late preterm neonates.

The American Academy of Pediatrics and the Canadian Paediatric Society both advise that all newborns should undergo bilirubin screening before leaving the hospital, and this has become the standard practice in both countries. However, the US Preventive Task Force has found no strong evidence to suggest that this practice of universal screening for bilirubin reduces the occurrence of significant outcomes such as bilirubin-induced neurologic dysfunction or kernicterus. To evaluate the effectiveness of transcutaneous screening compared to visual inspection for hyperbilirubinemia to prevent the readmission of newborns (infants greater than 35 weeks' gestation) for phototherapy. We searched CENTRAL, MEDLINE, Embase, CINAHL, ClinicalTrials.gov, ICTRP, and ISRCTN in June 2023. We also searched conference proceedings, and the reference lists of included studies. We included randomized controlled trials (RCTs), quasi-randomized, cluster-randomized, or prospective cohort studies with control arm that evaluated the use of transcutaneous bilirubin (TcB) screening for hyperbilirubinemia in newborns before hospital discharge. We used standard methodologic procedures expected by Cochrane. We evaluated treatment effects using a fixed-effect model with risk ratio (RR) and 95% confidence intervals (CI) for categorical data and mean, standard deviation (SD), and mean difference (MD) for continuous data. We used the GRADE approach to evaluate the certainty of evidence. We identified one RCT (1858 participants) that met our inclusion criteria. The study included 1858 African newborns at 35 weeks' gestation or greater who were receiving routine care at a well-baby nursery, and were randomly recruited prior to discharge to undergo TcB screening. The study had good methodologic quality. TcB screening versus visual assessment of hyperbilirubinemia in newborns: - may reduce readmission to the hospital for hyperbilirubinemia (RR 0.25, 95% CI 0.14 to 0.46; P < 0.0001; moderate-certainty evidence); - probably has little or no effect on the rate of exchange transfusion (RR 0.20, 95% CI 0.01 to 14.16; low-certainty evidence); - may increase the number of newborns who require phototherapy prior to discharge (RR 2.67, 95% CI 1.56 to 4.55; moderate-certainty evidence). - probably has little or no effect on the rate of acute bilirubin encephalopathy (RR 0.33, 95% CI 0.01 to 8.18; low-certainty evidence). The study did not evaluate or report cost of care. Moderate-certainty evidence suggests that TcB screening may reduce readmission for hyperbilirubinemia compared to visual inspection. Low-certainty evidence also suggests that TcB screening probably has little or no effect on the rate of exchange transfusion compared to visual inspection. However, moderate-certainty evidence suggests that TcB screening may increase the number of newborns that require phototherapy before discharge compared to visual inspection. Low-certainty evidence suggests that TcB screening probably has little or no effect on the rate of acute bilirubin encephalopathy compared to visual inspection. Given that we have only identified one RCT, further studies are necessary to determine whether TcB screening can help to reduce readmission and complications related to neonatal hyperbilirubinemia. In settings with limited newborn follow-up after hospital discharge, identifying newborns at risk of severe hyperbilirubinemia before hospital discharge will be important to plan targeted follow-up of these infants.

Cost-effectiveness analysis of alternative screening strategies for the detection of cervical cancer among women in rural areas of Western Kenya.

While the incidence of cervical cancer has dropped in high-income countries due to organized cytology-based screening programs, it remains the leading cause of cancer death among women in Eastern Africa. Therefore, the World Health Organization (WHO) now urges providers to transition from widely prevalent but low-performance visual inspection with acetic acid (VIA) screening to primary human papillomavirus (HPV) DNA testing. Due to high HPV prevalence, effective triage tests are needed to identify those lesions likely to progress and so avoid over-treatment. To identify the optimal cost-effective strategy, we compared the VIA screen-and-treat approach to primary HPV DNA testing with p16/Ki67 dual-stain cytology or VIA as triage. We used a Markov model to calculate the budget impact of each strategy with incremental quality-adjusted life years and incremental cost-effectiveness ratios (ICER) as the main outcome. Deterministic cost-effectiveness analyses show that the screen-and-treat approach is highly cost-effective (ICER 2469 Int$), while screen, triage, and treat with dual staining is the most effective with favorable ICER than triage with VIA (ICER 9943 Int$ compared with 13,177 Int$). One-way sensitivity analyses show that the results are most sensitive to discounting, VIA performance, and test prices. In the probabilistic sensitivity analyses, the triage option using dual stain is the optimal choice above a willingness to pay threshold of 7115 Int$ being cost-effective as per WHO standards. The result of our analysis favors the use of dual staining over VIA as triage in HPV-positive women and portends future opportunities and necessary research to improve the coverage and acceptability of cervical cancer screening programs.

A Novel Method on Wound Identification using Machine Learning and Image Processing

Automated wound detection using advanced computer vision techniques has emerged as a promising avenue within the realm of healthcare. This approach offers a streamlined and accurate means of identifying a variety of acute injuries, including bruises, abrasions, and traumatic wounds. Wound identification and assessment are crucial tasks in medical practice, facilitating appropriate treatment planning and monitoring of patient recovery. Traditional methods of wound assessment often rely on visual inspection by healthcare professionals, which can be subjective and time-consuming. In recent years, advances in machine learning (ML) and image processing have offered promising avenues for automating wound identification and analysis. This paper presents a comprehensive review of existing techniques and proposes a novel approach that leverages ML algorithms and image processing methods for accurate wound identification. We discuss various challenges, such as data variability, and provide insights into future research directions to enhance the efficacy and applicability of automated wound identification systems. In this study, we delve into the application of YOLO v8, a cutting-edge real-time object detection framework, for automated wound detection across diverse clinical scenarios