Precise Identification Of Individuals Research Articles

Recognition of Facial Expression with the Help of IoT, AI and Robotics

The emerging field of "Smart Face Recognition" utilizes IoT and machine learning to accurately identify individuals based on their facial characteristics. Various industries such as security, retail, and healthcare are leveraging this technology to enhance customer satisfaction and increase productivity. By combining IoT and machine learning, large amounts of data can be collected from multiple sources, such as cameras and sensors, and used to train algorithms for real-time, precise identification of individuals. This technology is gaining popularity due to its accuracy, speed, and scalability, making it essential for applications like security and access control. Recognizing human facial emotions is a key focus in today's technological landscape, with robotic applications across various sectors highlighting the importance of emotion recognition for effective human-robot interaction. This project aims to develop and implement a new automated system for emotion detection and facial recognition using Artificial Intelligence (AI) and the Internet of Things (IoT).

MAFLD identifies patients with significant hepatic fibrosis better than MASLD.

Diagnostic criteria for metabolic dysfunction-associated steatotic liver disease (MASLD) have been proposed but not yet validated. This study aimed to compare the diagnostic accuracy of the MASLD definition with the existing criteria for metabolic dysfunction-associated fatty liver disease (MAFLD) in identifying patients with significant fibrosis. The analysis included a total of 8317 individuals who had complete biochemical and liver ultrasonography data from the National Health and Nutrition Examination Survey (2017-2020). In this study, significant fibrosis (≥ F2) was determined by a median liver stiffness of ≥ 8.0kPa. To identify independent factors associated with significant fibrosis, multivariable logistic regression analyses were applied. MAFLD (OR 3.44; 95% CI 2.88-4.12; P < 0.0001) has a trend for stronger and independent association with significant fibrosis compared to MASLD (OR 2.63; 95% CI 2.22-3.11; P < 0.0001). Non-MASLD MAFLD is independently associated with a 14.28-fold higher odds of significant fibrosis compared to non-MAFLD MASLD. The sensitivity for detecting significant fibrosis for MAFLD and MASLD was 76.23% vs 69.94%, respectively. The performance of MAFLD remains consistent in a sub-analysis of patients with no or mild alcohol intake. The definition of MAFLD provides a more precise identification of individuals who have both fatty liver and significant fibrosis, assessed by non-invasive tests.

Predictors of Frailty Change in Home and Community-Based Services Populations

With unprecedented demand for Medicaid long-term services and supports, states are seeking to allocate resources in the most efficient way. Understanding the prevalence of frailty and how it varies across home and community-based services (HCBS) populations can assist states with more precise identification of individuals most in need of services. Early identification of individuals more likely to experience frailty changes could allow for enhanced care planning to prevent or slow the progression of decline. Longitudinal study. Data from Connecticut's assessment tool (based on interRAI-HC) were analyzed at 2 time points for 16,309 individuals receiving HCBS. The sample included assessments completed between November 1, 2017 and July 15, 2020 across 4 groups: older adults 65+ years old meeting nursing facility level of care (NF LOC), older adults 65+ years old not meeting NF LOC, individuals with acquired brain injury, and individuals <65years old with physical disability. We measured frailty using the Frailty Index (FI) and examined change in FI between baseline and follow-up. A change in FI score of at least ±0.03 was classified as a clinically meaningful change. We compared predictors of clinically meaningful decline or improvement using multivariate logistic regression. In our sample, 54% of individuals experienced a clinically meaningful change: 42% declined and 12% improved. Individuals receiving in-home care services had lower odds of improvement across all HCBS groups and multiple frailty categories with odds ratios ranging from 0.35 to 0.68. Frail older adults 65+ years old meeting nursing facility level of care receiving physical therapy were 21% less likely to experience decline and 1.4 times more likely to improve. The nature of HCBS support provided can impact changes in frailty status. More reactive services such as in-home care may contribute to frailty decline while rehabilitative services such as physical therapy may protect against decline.

Type of HCBS Support Provided Predictive of Frailty Status Change Among Older Participants

With demand for Medicaid long-term services and supports increasing nationwide, states are seeking ways to ensure resources are allocated to individuals who most need them. States have implemented assessment tools and algorithms to prioritize individuals most at risk for institutionalization or high service utilization. Frailty, a state of physical vulnerability associated with greater disability and increased healthcare utilization among older adults, has gained significant attention in recent years within medical literature. However, the use of frailty in social service systems has largely been limited to epidemiologic studies of populations receiving home and community-based services (HCBS). Understanding the prevalence of frailty and how it varies may assist with more precise identification of individuals most in need of services. Early identification of these individuals may allow for enhanced care planning to prevent or slow the progression of decline.

Role of Cardiac Biomarkers in Epidemiology and Risk Outcomes.

The use of biomarkers associated with cardiovascular disease (CVD) is established for diagnostic purposes. Cardiac troponins, as specific markers of myocardial injury, and natriuretic peptides, reflecting myocardial dilation, are routinely used for diagnosis in clinical practice. In addition, a substantial body of research has shed light on the ability of biomarkers to reflect the risk of future major cardiovascular events. Among biomarkers, troponin and members of the natriuretic peptide family have been investigated extensively in the general population, in those at higher risk, and in patients with known CVD. Both biomarkers have been shown to contribute substantially to statistical models describing cardiovascular risk, in addition to and independently of important clinical characteristics. The more precise identification of individuals at risk by appropriate use of biomarkers might lead to an earlier initiation of preventive therapies and potentially avoid significant events. We summarize the current evidence concerning risk prediction using cardiac biomarkers at different stages in the development of CVD and provide examples of observational studies and large-scale clinical trials testing such application. Beyond the focus on troponin and natriuretic peptides, we also discuss other important and emerging biomarkers in the field with potential for such application, including growth differentiation factor-15, soluble ST2 (alias for IL1RL1 [interleukin 1 receptor like 1), and galectin-3. Incorporating biomarkers in risk prediction models might allow more precise identification of individuals at risk. Among the various biomarkers, cardiac troponin appears to be the most promising for prediction of future cardiovascular events in a wide variety of patient populations.

Machine Learning Approaches Reveal Metabolic Signatures of Incident Chronic Kidney Disease in Individuals With Prediabetes and Type 2 Diabetes.

Early and precise identification of individuals with prediabetes and type 2 diabetes (T2D) at risk for progressing to chronic kidney disease (CKD) is essential to prevent complications of diabetes. Here, we identify and evaluate prospective metabolite biomarkers and the best set of predictors of CKD in the longitudinal, population-based Cooperative Health Research in the Region of Augsburg (KORA) cohort by targeted metabolomics and machine learning approaches. Out of 125 targeted metabolites, sphingomyelin C18:1 and phosphatidylcholine diacyl C38:0 were identified as candidate metabolite biomarkers of incident CKD specifically in hyperglycemic individuals followed during 6.5 years. Sets of predictors for incident CKD developed from 125 metabolites and 14 clinical variables showed highly stable performances in all three machine learning approaches and outperformed the currently established clinical algorithm for CKD. The two metabolites in combination with five clinical variables were identified as the best set of predictors, and their predictive performance yielded a mean area value under the receiver operating characteristic curve of 0.857. The inclusion of metabolite variables in the clinical prediction of future CKD may thus improve the risk prediction in people with prediabetes and T2D. The metabolite link with hyperglycemia-related early kidney dysfunction warrants further investigation.

Abstract A049: Program for the identification, management and monitoring of patients and families at high risk of cancer in a Colombian National Cancer Reference Institution

Abstract Cancer is the second cause of mortality due to noncommunicable diseases in Colombia. In 2015 incident cases of breast (BC), gastric (GC), colorectal (CRC), and ovarian cancer (OC) attended at the Colombian National Cancer Institute (NCI) were 685, 498, 470, and 127, respectively. Although hereditary cancer syndromes are the minority of all cancer cases, the precise identification of individuals and relatives at high risk is a key aspect to the implementation of surveillance/screening, chemoprevention, and preventive surgery strategies for affected and unaffected carriers. In our country there are few studies conducted on hereditary cancer, and little is known about the spectrum of syndromes affecting Colombian families. In the Colombian NCI, we have designed and develop a comprehensive program for the registration, identification, diagnosis, management, and surveillance of cancer cases at high risk. Two main strategies where defined within this pilot program: 1) adjustment of the international protocols to the institutional context for identification and referral criteria of cancer patients with suspected syndrome to genetic counseling, genetic testing criteria, management, and surveillance, and 2) implementation of an institutional registry of patients with hereditary cancer, among other strategies. Also, first-degree relatives (FDR) of the affected carriers are offered to be tested and followed through the Center for Cancer Prevention and Early Detection (CPRED), recently established by the Colombian NCI. This Institutional ongoing program is providing genetic risk assessment to an average of 20 cancer patients per week since April 2018. The most frequent cancer we have attended is BC (56%), followed by CRC (10.5%), OC (6%), GC (5.5%), and others (22%). The average age at diagnosis was 47.3 for BC, 50.6 for CRC, 33.6 for OC, 39.4 for GC, and 47.8 years old (yo) for other cancers. Genetic testing has been offered to the patients according to the international guidelines. From all BC cases, the following fulfilled the Hereditary Breast and Ovarian Cancer (HBOC) criteria: i) 44.3% were diagnosed ≤ 45 yo, ii) 24% were diagnosed with triple-negative breast cancer (TNBC) at ≤ 60 yo, iii) 4% were TNBC cases diagnosed at &amp;gt; 60 yo + ≥ 1 FDR/second-degree relative with BC at &amp;lt; 50 yo, iv) 8% were patients with bilateral BC, v) 4% had a second primary tumor, and vi) 1.3% had Ashkenazi Jewish ancestry. From CRC cases, 50% were diagnosed at &amp;lt; 50 yo regardless of family history of gastrointestinal cancers and 30% were diagnosed at ≥ 50 yo and fulfilled criteria for Lynch or Li Fraumeni syndromes. In the case of GC, 60% of the patients had diffuse gastric cancer subtype at &amp;lt; 50 yo. Finally, all OC cases were submitted for genetic testing since all were diagnosed at &amp;lt; 50 yo; 43% were tested for HBOC since they corresponded to papillary serous subtype and 29% fulfilled criteria for Peutz Jeghers syndrome. To our knowledge, this is the first genetic cancer risk assessment program in the country, based in the largest Colombian cancer hospital. Citation Format: María Carolina Sanabria-Salas, Gonzalo Guevara-Pardo, Antonio Huertas, Vilma Medina, Ana Lucía Rivera-Herrera, Juan Carlos Mejía, Jesús Acosta, Carolina Wiesner-Ceballo. Program for the identification, management and monitoring of patients and families at high risk of cancer in a Colombian National Cancer Reference Institution [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr A049.

Paradigm changing evidence that alter tuberculosis perception and detection: Focus on latency

Tuberculosis remains a devastating disease to Mankind, ranking as the ninth cause of death worldwide. Eliminating tuberculosis as proven much more difficult than once anticipated. In addition to the delay in diagnosis and drug resistance problems that compromise the efficacy of treatment, the enormous reservoir of latently infected individuals continuously feeds the epidemics. However, targeting latency with prophylactic antibiotic administration is not possible at the populational level. Together, these issues call for a better understanding of latency, as well as for a more precise identification of individuals at high risk of reactivation. For this, recent paradigm changing evidence need to be taken into account, most notably, the existence of a tuberculosis spectrum; the genetic diversity of both humans and tuberculosis-causing bacteria; and the changes in the human population that interfere with tuberculosis. Here we discuss latency in the light of these variables and how that understanding can move forward tuberculosis research and elimination.

Precision medicine for suicidality: from universality to subtypes and personalization

Precision medicine for suicidality: from universality to subtypes and personalization

Personality features in ultra-high risk for psychosis: A comparative study with schizophrenia and control subjects using the Temperament and Character Inventory-Revised (TCI-R)

Several variables have been identified as risk factors for conversion to overt psychosis in ultra-high risk for psychosis (UHR) individuals. Although almost two-thirds of them do not experience a transition to psychosis, they still exhibit functional disabilities. Other subjective developmental features may be useful for a more precise identification of individuals at UHR. Avoidant behaviors are consistently reported in schizophrenia and in UHR individuals and may be the reflection of a pattern of personality. Thus, personality features in UHR individuals deserves further research. The objective of the present study was to compare temperament and character dimensions between UHR individuals, patients with schizophrenia and healthy controls. One hundred participants (25 UHR individuals, 25 schizophrenia patients and 50 control subjects) where evaluated with the Temperament and Character Inventory-Revised (TCI-R). Univariate ANOVAs followed by Bonferroni tests were used. UHR individuals and schizophrenia patients exhibited higher levels of Harm Avoidance (HA) when compared to control subjects. For HA1 Anticipatory worry vs Uninhibited optimism and HA4 Fatigability & asthenia, UHR and schizophrenia groups showed similar scores and both groups were higher compared to control subjects. With respect to Cooperativeness (CO), UHR and schizophrenia reported lower scores than control subjects, in particular CO2 Empathy vs Social disinterest and CO3 Helpfulness vs unhelpfulness. This study replicates and extends the consideration of HA as a psychopathological related endophenotype and gives us further information of the possible role of personality features in the expression of some of the social dysfunctions observed both in prodromal subjects and schizophrenia patients.

Application of microarray profiling to clinical trials in cancer

Cancer is a heterogeneous disease with variable biology and often unpredictable clinical outcomes. Current clinicopathologic staging is often unable to accurately predict which individuals will suffer systemic relapse after definitive loco regional treatment. In fact, many patients with early-stage disease will develop metastases within 10 years after treatment.1 Conversely, up to 30% of patients with high-risk cancer experience long-term disease-free survival with loco regional therapy alone. Risk reduction for relapse and death is unquestionably improved by adjuvant systemic therapy; however, the absolute benefits of adjuvant therapy is achieved in less than 15% of patients overall, and precise identification of individuals who will benefit from systemic therapy is not possible on clinical or pathologic grounds.2 The distressing fact is that most cancer patients are overtreated in the adjuvant setting to avoid missing those few who might achieve benefit.

DNA fingerprinting in cattle using oligonucleotide probes.

Oligonucleotide probes specific for simple tandem repeat sequences produce individual specific DNA fingerprints in man and all animal species tested so far. Here 11 different synthetic probes were hybridized to bovine genomic DNAs which had been digested with the restriction endonucleases HinfI, AluI and HaeIII. Two of these probes gave DNA fingerprint patterns which were analysed for three German breeds. Different parameters were calculated, such as the average number of bands per individual or the probability of finding identical fingerprints in two unrelated individuals. The number of polymorphic bands varies from 11 to 23 in the different breeds and the probability of finding the same banding pattern in two unrelated individuals ranges from 1.5 x 10(-7) to 2.4 x 10(-7). Hence this DNA fingerprinting procedure allows precise identification of individuals. It is also a useful additional method for paternity testing in cattle.