Complete Analysis Research Articles

Performance, Energy Consumption and Costs: A Comparative Analysis of Automatic Text Classification Approaches in the Legal Domain

The common practice in Machine Learning research is to evaluate the top-performing models based on their performance. However, this often leads to overlooking other crucial aspects that should be given careful consideration. In some cases, the performance differences between various approaches may be insignificant, whereas factors like production costs, energy consumption, and carbon footprint should be taken into account. Large Language Models (LLMs) are widely used in academia and industry to address NLP problems. In this study, we present a comprehensive quantitative comparison between traditional approaches (SVM-based) and more recent approaches such as LLM (BERT family models) and generative models (GPT2 and LLAMA2), using the LexGLUE benchmark. Our evaluation takes into account not only performance parameters (standard indices), but also alternative measures such as timing, energy consumption and costs, which collectively contribute to the carbon footprint. To ensure a complete analysis, we separately considered the prototyping phase (which involves model selection through training-validation-test iterations) and the in-production phases. These phases follow distinct implementation procedures and require different resources. The results indicate that simpler algorithms often achieve performance levels similar to those of complex models (LLM and generative models), consuming much less energy and requiring fewer resources. These findings suggest that companies should consider additional considerations when choosing machine learning (ML) solutions. The analysis also demonstrates that it is increasingly necessary for the scientific world to also begin to consider aspects of energy consumption in model evaluations, in order to be able to give real meaning to the results obtained using standard metrics (Precision, Recall, F1 and so on).

Assessing the Effectiveness and Security Implications of AI Code Generators

Students, especially those outside the field of cybersecurity, are increasingly turning to Large Language Model (LLM)-based generative AI tools for coding assistance. These AI code generators provide valuable support to developers by generating code based on provided input and instructions. However, the quality and accuracy of the generated code can vary, depending on factors such as task complexity, the clarity of instructions, and the model’s familiarity with the programming language. Additionally, these generated codes may inadvertently utilize vulnerable built-in functions, potentially leading to source code vulnerabilities and exploits. This research undertakes an in-depth analysis and comparison of code generation, code completion, and security suggestions offered by prominent AI models, including OpenAI CodeX, CodeBert, and ChatGPT. The research aims to evaluate the effectiveness and security aspects of these tools in terms of their code generation, code completion capabilities, and their ability to enhance security. This analysis serves as a valuable resource for developers, enabling them to proactively avoid introducing security vulnerabilities in their projects. By doing so, developers can significantly reduce the need for extensive revisions and resource allocation, whether in the short or long term.

Early Low-Grade Inflammation Induced by High-Salt Diet in Sprague Dawley Rats Involves Th17/Treg Axis Dysregulation, Vascular Wall Remodeling, and a Shift in the Fatty Acid Profile.

Unrestricted increased table salt (NaCl) intake is associated with oxidative stress and inflammation, leading to endothelial dysfunction and atherosclerosis. However, data on salt-induced immunomodulatory effects in the earliest phase of salt loading are scarce. In the present study, an animal model of short-term salt loading was employed, including male Sprague Dawley rats consuming a high-salt diet (HSD; 4% NaCl) or standard laboratory chow (low-salt; LSD; 0.4% NaCl) during a 7-day period. The contribution of angiotensin II (ANGII) suppression was tested by adding a group of rats on a high-salt diet receiving ANGII infusions. Samples of peripheral blood/mesenteric lymph node leukocytes, brain blood vessels, and serum samples were processed for flow cytometry, quantitative real-time PCR, total proteome analysis, and multiplex immunoassay. Data analysis revealed the up-regulation of Il 6 gene in the microcirculation of high-salt-fed rats, accompanied by an increased serum level of TNF-alpha cytokine. The high-salt diet resulted in increased proportion of serum mono-unsaturated fatty acids and saturated fatty acids, reduced levels of linoleic (C18:2 ω-6) and α-linolenic (C18:3 ω-3) acid, and increased levels of palmitoleic acid (C16:1 ω-7). The high-salt diet had distinct, lymphoid compartment-specific effects on leukocyte subpopulations, which could be attributed to the increased expression of salt-sensitive SGK-1 kinase. Complete proteome analysis revealed high-salt-diet-induced vascular tissue remodeling and perturbations in energy metabolism. Interestingly, many of the observed effects were reversed by ANGII supplementation. Low-grade systemic inflammation induced by a HSD could be related to suppressed ANGII levels. The effects of HSD involved changes in Th17 and Treg cell distribution, vascular wall remodeling, and a shift in lipid and arachidonic acid metabolism.

A simple model of nutrient recycling and dormancy in a chemostat: Mathematical analysis and a second-order nonstandard finite difference method

A chemostat is an apparatus that sustains a homogeneous environment through continuous inflow and outflow. Presented is a chemostat model that characterizes the dynamics of dormancy-capable microorganisms. This model of coupled systems of nonlinear ordinary differential equations (ODEs) can apply to various types of organisms, such as different species of bacteria, archaea, algae, fungi, viruses, and protozoa. However, these species reside in different environments and rely on different sets of nutrients. Thus, the model adapts to each species’ limiting nutrient through nutrient recycling. This paper includes a complete stability analysis, supporting phase plane portraits, and accompanying bifurcation diagrams. The paper also proposes an advanced second-order, positivity-preserving, and elementary stable nonstandard finite difference method for solving the mathematical model. Series of numerical simulations are presented that support the theoretical results and explore different biological scenarios. The stability analysis reveals that (1) if the overall dilution, death, and conversion are less than the overall growth, both the dormant and active populations persist when introduced to a chemostat; and (2) if the overall dilution, death, and conversion are more than the overall growth, the microorganism population in its entirety will die off when introduced to a chemostat. Furthermore, the model study suggests that neither dormancy nor nutrient recycling provides substantial survival advantages in a basic chemostat when no threat to the active microorganism is present.

PVD coated dies in action: Exploring finite element analyses for sheet metal forming of high‐strength steel

AbstractThis research proposes a complete analysis of the use of physical vapour deposition coated dies in the sheet metal forming process for high‐strength‐steel sheets. The goal of the proposed approach is to investigate how PVD coatings affect die performance and how that affects the formability and quality of the high‐strength‐steel‐sheets that are made. The finite element analyses are used to simulate and evaluate the mechanical behaviour and deformation characteristics during the forming process. Studies to enhance the forming characteristics of these materials, typically denoted by limiting draw ratio and maximum punch force are required. A reduction in punch force required and improved limiting draw ratio is observed that is attributed to the enhanced contact with friction‐conditions in the die‐sheet interfaces. The experimental results are compared with simulation results from DD3IMP, a code used for deep drawing simulations, and it is evident that the experimental outcomes are analysed well with the simulation results.

Modeling of the Combined Effect of the Surface Roughness and Coatings in Contact Interaction

The model of indentation of a spherical punch with a rough surface into a thin elastic layer lying on an elastic half-space has been developed. A numerical-analytical solution is suggested based on the two-scales approach. At macroscale, the integral equation of the second kind is reduced to calculate the nominal contact characteristics, taking into account the surface layer thickness and its mechanical characteristics, as well as additional compliance due to surface roughness calculated from the microscale analysis. The influence of the punch roughness and the surface layer mechanical and geometrical characteristics on the nominal contact pressure distribution, on the nominal contact area and the indentation depth, as well as on the real contact area and pressures at the individual contact spots, is analyzed. The developed contact model can be used to analyze the indentation of the punch into the layered elastic base, taking into account the roughness of the punch surface, and can also be used to give a complete analysis of the roughness effect on the contact process at both scale levels. The results can be used to control the indentation of the rough-coated bodies.

Social cost--benefit analysis of solid waste management options with application to Mumbai, India.

Managing solid waste continues to be an environmental, technical and economic challenge, especially for developing countries. Though these countries' urban local bodies (ULBs) are moving up the waste management hierarchy, most waste is still openly dumped. One key reason for this choice is the non-accounting of (a) social costs associated with open dumping (OD) and (b) direct/indirect benefits of other options. The current study conducts a complete social cost-benefit analysis (SCBA) comparing OD to sanitary landfilling, composting, bio-methanation, incineration and gasification alternatives. The study finds that when only private costs/benefits are considered, a mix of OD and sanitary landfills is preferred; however, when external costs/benefits are factored in, the mix shifts towards alternatives like incineration and gasification. These learnings from the SCBA are then applied to Mumbai, which generates 9000 tonnes of waste daily. To determine the optimal mix for Mumbai ULB, a constrained optimization exercise is carried out considering the technical feasibility of the alternatives and the ULB's capital budget. The study finds that with the current practice of OD, the net present value (NPV) of the social costs over a 30-year horizon will be over US$ 6-9 billion. However, even if one-fifth of the ULB's capital budget is allocated towards other waste management alternatives, the mix would shift towards sophisticated technologies and the NPV of social costs would reduce to around half that amount.

The significance of multipole interactions for the stability of regular structures composed from charged particles

Identifying the forces responsible for stabilising binary particle lattices is key to the controlled fabrication of many new materials. Experiments have shown that the presence of charge can be integral to the formation of ordered arrays; however, a complete analysis of the forces responsible has not included many of the significant lattice types that may form during fabrication. A theory of many-body electrostatic interactions has been applied to six lattice stoichiometries, AB, AB2, AB3, AB4, AB5 and AB6, to show that induced multipole interactions can make a very significant (>80 %) contribution to the total lattice energy of arrays of charged particles. Particle radii ratios which favour global minima in electrostatic energy are found to be the same or a close match to those observed by experiment. Although certain lattice types exhibit local energy minima, the calculations show that many-body rather than two-body interactions are ultimately responsible for the structures observed by experiment. For a lattice isostructural with CFe4, a particle size ratio not previously observed is found to be particularly stable due to many-body effects.

Pengaruh Media Papan Perkalian Terhadap Hasil Belajar Matematika Siswa Kelas III SD YPK Elim Kota Sorong

The purpose of this study was to determine the Influence of Multiplication Board Media on Mathematics Learning Outcomes of Grade III Students of SD YPK Elim Sorong City. This type of research uses Quantitative Research with the research design used is a pre-experimental design with the type One-Group Pretest-posttest. The population is class III A students with a total of 19 students with a sampling technique carried out by nonprobability sampling, namely purporsive sampling. The instruments used are observation sheets and essay tests to measure student learning outcomes, while the results of the analysis of student learning completeness on the average posttest score are 83.84. The reliability test results obtained by Cronbachs Alpha for student responses amounted to 0.852 which means it has a high level of reliability with the normality test of student posttest learning outcomes having a significance level of 0.028 > 0.05. The hypothesis test obtained tcount of 7.001 with df = n – 1 (19-1=18) obtained ttable of 1.729. Based on the results of the analysis of value data, namely tcalculate > ttable (-7.001> 1.729), with a magnitude of significance level of 0.05, the hypothesis is accepted. Thus, it can be concluded that there is an influence of Multiplication Board Media on the Mathematics Learning Outcomes of Grade III Students of SD YPK Elim Malanu in Sorong City.

Regional history and political history: possible interfaces between two approaches

This work addresses the transformation in the approach to History that occurred in 1929 with the creation of the Revista dos Annales, led by Marc Bloch and Lucien Febvre. This paradigmatic shift broke with the tradition of focusing only on major historical events and figures, adopting a broader, interdisciplinary approach that incorporated anthropology, sociology, and geography into historical analysis. Political history, which had been disregarded by the Annales, underwent a revival in the 1970s, reintroducing it as an important field of study. It also highlights the importance of considering the regional dimension in the analysis of political history, recognizing that the politician creates his own spatiality and that regional politics plays a significant role in the formation of identities and specific political practices. The regional approach enriches our understanding of politics by connecting the particular to the universal, allowing for a more complete and interdisciplinary analysis of historical phenomena. In summary, the text emphasizes the importance of considering the interconnection between regional history and political history for a deeper understanding of society over time.

QSAR modelling to predict structural features of certain sulfonamide as Urokinase-type Plasminogen Activator inhibitors

The serine hydrolase family includes serine proteases. It is essential for hydrolyzing protein peptide bonds and breaking them. The urokinase-type plasminogen activator (uPA) selectively binds to the uPAR on numerous cell types, including cancer cells. Pericellular proteolysis of cell-bound proteins requires this interaction. High uPA and uPAR levels regularly worsen cancer prognoses. Thus, small chemical active-site inhibitors that block uPA may diminish cancer cell invasion and metastasis. In compliance with Organization for Economic Corporation and Development guidelines, this research performed a complete Quantitative structure activity relationship analysis of sulfonamide compounds as Urokinase-type Plasminogen Activator inhibitors. Py-Descriptors were used for this investigation. PyDescriptor uses PyMOL standards and idioms to calculate 11,145 simple molecular descriptors. This plugin calculates molecular descriptors irrespective of molecular representation properties like atom numbering or labelling, spatial reference frame, translational and rotational invariance, etc. The investigation sought to find essential and hidden structural characteristics that regulate sulfonamide-type drugs' Urokinase-type Plasminogen Activator Inhibitory action. Twenty-eight sulfonamide chemicals are used in the Quantitative structure activity relationship study to generate statistically robust and highly predictive univariate and multivariate models. All models were thoroughly evaluated and meet several statistical parameter thresholds (e.g., R2 =0.9259–0.9280, Q2Loo= 0.8579–0.8558, Q2LMO= 0.8013–0.7865). The analysis reveal that occurance of ring carbon atoms exactly at 3 A0 from carbon atom, number of negatively charged atoms from sulphur atoms within 5 bonds, presence of hydrogen atom exactly at 3 bonds from donar atoms, presence of carbon atom exactly at 4 A0 from donar atom, presence of acceptor atom exactly at 5 A0 from sulphur atom and sum of partial charges of lipo atoms within 6 bonds from sulphur atom are important pharmacophoric features for Urokinase-type Plasminogen Activator Inhibition binding affinity. Thus, the developed Quantitative structure activity relationship study has an equilibrium of quantitative and qualitative tactics. The results could be useful for future optimizations of sulfonamide analogues.

Analysis of a Graphene FET-Based Frequency Doubler for Combined Sensing and Modulation through Compact Model Simulation

The ambipolar conduction property of graphene field-effect transistors (GFETs) and the inherent square-like dependence of the drain current on the gate voltage, enable the development of single-device architectures for analog nonlinear radiofrequency (RF) circuits. The use of GFETs in novel RF component topologies allows leveraging graphene’s attractive thermal and mechanical properties to improve the miniaturization and weight reduction of electronic components. These features are specifically appealing for integrated sensing, modulation, and transmission systems. However, given the innovative nature of emerging graphene-based technology, a complete performance analysis of any novel electronic component is essential for customizing the operating conditions accordingly. This paper presents a comprehensive circuital analysis of a GFET-based frequency doubler, exploiting a compact model for GFET circuit simulation to assess the device’s performance parameters, including power conversion gain bandwidth and saturation. The performed analysis proposes to support the design of GFET-based harmonic transponders, offering integrated sensing and signal manipulation capabilities.

Toxicology, pharmacokinetics, and immunogenicity studies of CCR4-IL2 bispecific immunotoxin in rats and minipigs

We have developed a diphtheria toxin-based recombinant human CCR4-IL2 bispecific immunotoxin (CCR4-IL2-IT) for targeted therapy of cutaneous T-cell lymphoma (CTCL). CCR4-IL2-IT demonstrated superior efficacy in an immunodeficient mouse CTCL model. Recently, we have compared the in vivo efficacy of CCR4-IL2-IT versus Brentuximab (FDA approved leading drug in CTCL market) in the same immunodeficient mouse CTCL model. The comparison demonstrated that CCR4-IL2-IT was significantly more effective than Brentuximab. In this study, we have performed non-GLP (Good Laboratory Practice) toxicology, pharmacokinetics, immunogenicity studies of CCR4-IL2-IT in both rats and minipigs. CCR4-IL2-IT demonstrated excellent safety profiles in both rats and minipigs. The maximum tolerated dose of CCR4-IL2-IT was determined as 0.4 mg/kg in both rats and minipigs. Complete blood count and chemistry analysis did not show significant difference for all measured parameters between the blood samples of pre-injection versus post-injection from the five-day toxicology studies of CCT4-IL2-IT in both rats and minipigs. Histology analysis did not show difference between the PBS treatment group versus CCR4-IL2-IT treatment group at 50 μg/kg in both rats and minipigs. The half-life of CCR4-IL2-IT was determined as about 45 min in rats and 30 min in minipigs. The antibodies against CCR4-IL2-IT were detected in about two weeks after CCR4-IL2-IT treatment. CCR4-IL2-IT did not induce cytokine release syndrome in a peripheral blood mononuclear cell derived humanized mouse model. The depletion of CCR4+ cell and CD25+ cell (two target cell populations of CCR4-IL2-IT) was observed in minipigs. The excellent safety profile promoted us to further develop CCR4-IL2-IT towards clinical trials.

Exploring the Association Between Physical Activity and Cognitive Function Among People Living with Dementia.

Physical activity preserves cognitive function in people without dementia, but the relationship between physical activity and cognitive domains among people living with dementia is unclear. The objective of this study was to explore the association between physical activity and cognition domains among people living with dementia. Participants living with dementia in residential care facilities (complete case analysis: n = 24/42) completed a battery of cognitive tests (global cognition: Montreal Cognitive Assessment; executive function: Trail-Making Test, Digit Span Forward Test; perception and orientation: Benton Judgement of Line Orientation Test; language: Boston Naming Test; learning and memory: Rey Auditory Verbal Learning Test; complex attention: Digit Symbol Substitution Test). Participants wore an actigraphy monitor on their non-dominant wrist over seven days. We conducted a linear regression for total physical activity (independent variable) with race (white/black), fall risk (Morse Fall Scale), and the number of comorbidities (Functional Comorbidities Index) as covariates, and cognitive tests as variables of interest. Participants were primarily male (75%), white (87.5%), and 50%had unspecified dementia (Alzheimer's disease: 33%). Greater physical activity was associated with poorer global cognition, better executive function, and better learning and memory (ps < 0.05). Physical activity was not related to visuospatial perception, language, or complex attention. Physical activity may preserve executive function and learning and memory among people living with dementia. Wandering is more common in later stages of dementia, which may explain greater physical activity observed with lower global cognition. Regularly assessing physical activity may be useful in screening and monitoring cognitive changes.

Effect of Running Speed on Knee Biomechanics in Collegiate Athletes Following Anterior Cruciate Ligament Reconstruction.

Athletes after anterior cruciate ligament reconstruction (ACLR) demonstrate altered surgical knee running kinematics and kinetics compared with the nonsurgical limb and healthy controls. The effect of running speed on biomechanics has not been formally assessed in athletes post-ACLR. The purpose of this study was to characterize how knee biomechanics change with running speed between 3.5-7 (EARLY) and 8-13 (LATE) months post-ACLR. Fifty-five Division I collegiate athletes post-ACLR completed running analyses (EARLY: n = 40, LATE: n = 41, both: n = 26) at 2.68, 2.95, 3.35, 3.80, and 4.47 m·s -1 . Linear mixed-effects models assessed the influence of limb, speed, time post-ACLR, and their interactions on knee kinematics and kinetics. A significant limb-speed interaction was detected for peak knee flexion, knee flexion excursion, and rate of knee extensor moment ( P < 0.02), controlling for time. From 3.35 to 4.47 m·s -1 , knee flexion excursion decreased by -2.3° (95% confidence interval, -3.6 to -1.0) in the nonsurgical limb and -1.0° (95% confidence interval, -2.3 to -0.3) in the surgical limb. Peak vertical ground reaction force, peak knee extensor moment, and knee negative work increased similarly with speed for both limbs ( P < 0.002). A significant limb-time interaction was detected for all variables ( P < 0.001). Accounting for running speed, improvements in all surgical limb biomechanics were observed from EARLY to LATE ( P < 0.001), except for knee flexion at initial contact ( P = 0.12), but between-limb differences remained ( P < 0.001). Surgical and nonsurgical knee biomechanics increase similarly with speed in collegiate athletes at EARLY and LATE, with the exception of peak knee flexion, knee flexion excursion, and rate of knee extensor moment. Surgical knee biomechanics improved from EARLY and LATE, but significant between-limb differences persisted.

Proportional-retarded control of a quasi-zero-stiffness vibration isolator

This paper explores the control design and performance analysis of an active quasi-zero-stiffness vibration isolator utilizing the proportional-retarded (PR) control architecture. The PR architecture replaces the conventional “derivative” term in the proportional-derivative (or displacement-velocity) controller with the novel “retarded (time-delayed)” term, which is a new and effective way of active vibration suppression. Comprehensive gain-delay conjoint regulation strategies are developed for the strengthened isolation performance. For impact excitations, a complete stability analysis is conducted near the equilibrium position. Furthermore, a parameterized dominant pole placement algorithm is proposed to optimize the transient response of the PR-actuated isolator. Focusing on the rectangular pulse and long-duration step impacts, the algorithm adjusts the dominant poles to optimize the transient performance metrics, including the maximum displacement overshoot, steady-state displacement overshoot, and settling time. Regarding harmonic excitations, the delay-coupled effect is scrutinized for better low-frequency isolation performance, including the resonance frequency, nonlinear steady-state amplitude, multiple steady-state bands and nonlinearity elimination, equivalent active damping and stiffness, and absolute displacement transmissibility. In the case of random excitations, we demonstrate the superiority of the PR structure over the passive system.

MRI-based tumor shrinkage patterns after early neoadjuvant therapy in breast cancer: correlation with molecular subtypes and pathological response after therapy

BackgroundMRI-based tumor shrinkage patterns (TSP) after neoadjuvant therapy (NAT) have been associated with pathological response. However, the understanding of TSP after early NAT remains limited. We aimed to analyze the relationship between TSP after early NAT and pathological response after therapy in different molecular subtypes.MethodsWe prospectively enrolled participants with invasive ductal breast cancers who received NAT and performed pretreatment DCE-MRI from September 2020 to August 2022. Early-stage MRIs were performed after the first (1st-MRI) and/or second (2nd-MRI) cycle of NAT. Tumor shrinkage patterns were categorized into four groups: concentric shrinkage, diffuse decrease (DD), decrease of intensity only (DIO), and stable disease (SD). Logistic regression analysis was performed to identify independent variables associated with pathologic complete response (pCR), and stratified analysis according to tumor hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) disease subtype.Results344 participants (mean age: 50 years, 113/345 [33%] pCR) with 345 tumors (1 bilateral) had evaluable 1st-MRI or 2nd-MRI to comprise the primary analysis cohort, of which 244 participants with 245 tumors had evaluable 1st-MRI (82/245 [33%] pCR) and 206 participants with 207 tumors had evaluable 2nd-MRI (69/207 [33%] pCR) to comprise the 1st- and 2nd-timepoint subgroup analysis cohorts, respectively. In the primary analysis, multivariate analysis showed that early DD pattern (OR = 12.08; 95% CI 3.34–43.75; p < 0.001) predicted pCR independently of the change in tumor size (OR = 1.37; 95% CI 0.94–2.01; p = 0.106) in HR+/HER2− subtype, and the change in tumor size was a strong pCR predictor in HER2+ (OR = 1.61; 95% CI 1.22–2.13; p = 0.001) and triple-negative breast cancer (TNBC, OR = 1.61; 95% CI 1.22–2.11; p = 0.001). Compared with the change in tumor size, the SD pattern achieved a higher negative predictive value in HER2+ and TNBC. The statistical significance of complete 1st-timepoint subgroup analysis was consistent with the primary analysis.ConclusionThe diffuse decrease pattern in HR+/HER2− subtype and stable disease in HER2+ and TNBC after early NAT could serve as additional straightforward and comprehensible indicators of treatment response.Trial registration: Trial registration at https://www.chictr.org.cn/. Registration number: ChiCTR2000038578, registered September 24, 2020.

Gender-perceived workplace stressors by New Zealand construction professionals

The construction workplace is male-dominated and stressful, but little is known about gender-based differences in its stressors. This research examined the effect of gender and personal attributes on stressors in the New Zealand construction industry at four major levels: (1) individual, (2) group, (3) organizational, and (4) extra-organizational. Target respondents were professional construction members from Site Safe New Zealand, with 317 completed questionnaires and statistical analysis using the two-sample t-test, Kruskal-Wallis test, and Levene’s test. The findings show that females have higher qualifications than males, but males have about ten years more experience and more completed projects than their female counterparts. Males reported significantly higher technical skills than females and there was no significant difference between genders regarding sector involvement. At the individual level, females were most affected by role conflict stress and the perception of different treatment because of gender. Males felt significantly higher stress over the variable 'on/off-site office/administration building conditions’. At the group level, there were no significant gender differences, but sexual harassment warranted further investigation. Within the organizational and extra-organizational levels, no variables differed significantly between genders. The construction workforce has a strong gender imbalance and efforts are needed to address this through better work-life balance.

Prostate Cancer Detection Using Deep Learning and Traditional Techniques

Worldwide, men are affected by prostate cancer, which is a condition that is both common and has the potential to be fatal. Detection that is both timely and accurate is of the utmost importance for successfully treating patients and improving their outcomes. The technique of machine learning, which is a subfield of artificial intelligence, has recently emerged as a game-changing instrument for the identification of prostate cancer. The purpose of this work is to provide a complete overview and analysis of the use of machine learning methods in the detection, diagnosis, and prognosis of prostate cancer. The study that is being suggested makes use of a wide variety of datasets, which include genetic information, clinical records, and medical photographs. To guarantee the quality of the data, preprocessing techniques are used, and feature extraction techniques are utilized to assist the extraction of relevant information for the construction of models. There are several different machine learning algorithms that are being investigated to see whether they are effective in the identification of prostate cancer. These techniques include support vector machines (SVMs), convolutional neural networks (CNNs), and deep learning architectures. Several performance indicators, including accuracy, precision, recall, F1-score, and ROC-AUC, are taken into consideration throughout the training, validation, and assessment phases of our approach processes. In addition, the research covers ethical aspects, such as data protection, fairness, and the interpretability of models, which are essential for the use of machine learning solutions in healthcare settings. These findings provide evidence that machine learning has the potential to improve prostate cancer detection, which would allow for earlier diagnosis and more individualized therapy courses of treatment. In addition, the capacity to comprehend the predictions of the model and the openness of the model facilitate the ability of healthcare professionals to make educated judgements. This study contributes to the ever-changing environment of prostate cancer diagnosis by providing insights into the incorporation of machine learning into clinical practice. This, in turn, eventually leads to improvements in patient care and outcomes. To further advancing prostate cancer diagnosis and therapy, future approaches include the continuous development of models, the implementation of larger-scale clinical trials, and the utilization of developing technology respectively.

Validation of an Anti-Müllerian Hormone Cutoff for Polycystic Ovarian Morphology in the Diagnosis of Polycystic Ovary Syndrome in the HARMONIA Study: Protocol for a Prospective, Noninterventional Study.

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in women and is diagnosed using the Rotterdam criteria, including diagnosis of polycystic ovarian morphology (PCOM) by transvaginal ultrasound (TVUS). Due to high cost, availability, and the impact of the operator and ultrasound equipment on the reliability of the antral follicle count (AFC) by TVUS, an unmet need exists for a diagnostic test to determine PCOM without TVUS. A strong positive correlation between elevated anti-Müllerian hormone (AMH) levels and AFCs has been demonstrated in women with PCOS. In addition, recent updates to the international evidence-based PCOS guidelines state that serum AMH can be used as an alternative to TVUS-determined AFC, in the diagnosis of PCOM. The retrospective APHRODITE study derived and validated an AMH cutoff of 3.2 ng/mL for the Elecsys AMH Plus or Elecsys AMH assays (Roche) to diagnose PCOM in patients with PCOS. This study aims to further validate, in an independent prospective cohort, the AMH cutoff (3.2 ng/mL) for PCOM determination, which was previously derived and validated in the APHRODITE study. This large, prospective, multicenter, population-based, noninterventional study will evaluate the previously established AMH cutoff for the determination of PCOM during the diagnosis of PCOS using the Elecsys AMH Plus immunoassay in an independent population. Participants were women born between July 1985 and December 1987 in Northern Finland; the study partially links to the Northern Finland Birth Cohort 1986. We assessed the enrolled women, determined with the 2023 PCOS Guidelines, for current PCOS status and divided them by phenotype if positive. Each participant had 1 study visit to collect serum samples, record clinical data, and undergo a gynecological examination including TVUS. All data were collected by highly trained midwives or trained gynecologists. Sensitivity, specificity, and agreement measures were used to validate the previously determined cutoff in the whole population and in subpopulations based on phenotype and relevant demographic or clinical factors. The minimum target sample size was approximately 1800 women, including approximately 10% with PCOS. At the time of manuscript submission, participant recruitment had concluded, and 1803 women were enrolled into the study. Data collection is complete and biostatistical analysis is planned for 2023. To limit variability, there were few TVUS operators and only 2 TVUS machines of the same type. Additionally, all women who were taking oral contraceptives were excluded from the primary analysis population. Selection bias was limited as this was a population-based study and participants were not seeking treatment for PCOS symptoms. Validating the AMH cutoff in a large, population-based study will provide further evidence on the utility of the Elecsys AMH Plus or Elecsys AMH assays in PCOM diagnosis as an alternative to TVUS. Measuring AMH for PCOM diagnosis could reduce delayed or missed diagnoses due to operator-dependent TVUS examinations. ClinicalTrials.gov NCT05527353; http://tinyurl.com/2f3ffbdz. DERR1-10.2196/48854.