Geriatrics

Medicare

Latest AI and machine learning research in medicare for healthcare professionals.

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Geriatrics Subcategories: Alzheimer's Disease Medicare
Showing 961-980 of 3,588 articles

Data Resource Profile: Linking electronic health and social records to study and lower health inequalities in cardiovascular diseases (BIG-HEART)

The BIG-HEART cohort was established to study and reduce health inequalities in cardiovascular disease by linking rich, multidimensional electronic health and social data across Estonia. The dataset includes all individuals aged 36 and above residing in Estonia in 2012 (N= 770,323). Its full population coverage minimises sampling and healthy volunteer bias. Existing funding and permits will suppor...

Urethra contours on MRI: multidisciplinary consensus educational atlas and reference standard for artificial intelligence benchmarking

The urethra is a recommended avoidance structure for prostate cancer treatment. However, even subspecialist physicians often struggle to accurately identify the urethra on available imaging. Automated segmentation tools show promise, but a lack of reliable ground truth or appropriate evaluation standards has hindered validation and clinical adoption. This study aims to establish a reference-standa...

Zero-Shot Large Language Models for Long Clinical Text Summarization with Temporal Reasoning

Recent advances in large language models (LLMs) have shown potential in clinical text summarization, but their ability to handle long patient trajecto...

Automating Handwritten Vaccination Record Transcription with Generative Multimodal AI Models: A Proof of Concept Study from The Gambia

Handwritten home-based vaccination records (HBRs) are a vital source of immunization data, yet manual transcription in household surveys is time-consu...

Transforming Healthcare AI Education Through Micro-Learning: A Novel Partnership Model for Nursing Workforce Development

Healthcare professionals face an urgent need for AI literacy as artificial intelligence technologies rapidly transform clinical practice, yet nursing-...

Incidence of Long COVID Following Reinfection with COVID-19

COVID-19 reinfections have emerged as a critical concern, particularly in relation to post-acute sequelae of SARS-CoV-2 infection, commonly known as l...

Unsupervised Extractive Summarization of Psychedelic User Experience Reports

Contemporary psychedelic research highlights the value of user experience reports, yet their verbose, subjective nature poses challenges for clinical ...

Comparative Analysis of Long COVID and Post-Vaccination Syndrome: A Cross-Sectional Study of Clinical Symptoms and Machine Learning-Based Differentiation

Long COVID is a well-documented post-viral syndrome, while post-vaccination syndrome (PVS) remains poorly characterized. Understanding their similarit...

Spatial Distribution and Associated Factors Influencing 2024 Measles-Rubella Vaccination Campaign Coverage among Children Aged 9–59 Months in Mainland Tanzania

Globally, measles remains a major cause of child mortality, and rubella is the leading cause of birth defects among all infectious diseases. In Mainla...

Integrating Imaging-Derived Clinical Endotypes with Plasma Proteomics and External Polygenic Risk Scores Enhances Coronary Microvascular Disease Risk Prediction†

Coronary microvascular disease (CMVD) is an underdiagnosed but significant contributor to the burden of ischemic heart disease, characterized by angin...

Limited Predictability of Client Attendance in a Support Program for HIV Vertical Transmission Prevention: A Comparison of Machine Learning and Community Health Worker Predictions

Client attendance is vital for the success of HIV vertical transmission prevention programs, yet 23.4% of clients missed follow-up appointments after ...

Bayesian hybrid statistical and machine learning models for dengue forecasting in Bangladesh: Temporal and spatial analysis for an early warning system

Dengue remains a major public health concern in Bangladesh, yet reliable forecasting models that integrate climatic and demographic drivers are limite...

Privacy-Enhancing Sequential Learning under Heterogeneous Selection Bias in Multi-Site EHR Data

To develop privacy-enhancing statistical methods for estimation of binary disease risk model association parameters across multiple electronic health ...

TACO: TabPFN Augmented Causal Outcomes for Early Detection of Long COVID

Long COVID affects 10-40% of COVID-19 survivors, yet early detection remains challenging. We present TACO (TabPFN Augmented Causal Outcomes), a framew...

Prospective Evaluation of AI Risk Stratification for Triaging Expedited Screening Mammogram Interpretation

To prospectively evaluate the feasibility and performance of expedited screening mammogram interpretation for women identified as high-risk by a deep ...

When AI Meets the FDA: An Evaluation of Large Language Models Performance in Regulatory and Clinical Trial Data Extraction, Synthesis, and Analysis

Clinical and population decision-making relies on the systematic evaluation of extensive regulatory evidence. The FDA drug reviews provide detailed in...

Deep Learning Driven Field Dose Prediction for Head and Neck Cancer Treated with Spot Scanning Proton Therapy

Accurate dose prediction is essential for automating radiotherapy planning. In spot scanning proton therapy (SSPT), dose evaluation is required at bot...

Explainability in action: A metric-driven assessment of local explanations for healthcare tabular models

Explainable AI (XAI) is essential in clinical machine learning, yet quantitative evaluation of explanation quality is rarely reported in a reproducibl...

A Global Atlas of Digital Dermatology to Map Innovation and Disparities

The adoption of artificial intelligence in dermatology promises democratized access to healthcare, but model reliability depends on the quality and co...

Understanding Uncertainty in Large Language Model Predictions of Early Death in Critically Ill Patients: A Conformal Prediction Approach

Early prediction of in-hospital death remains a significant challenge due to the limited availability of structured data during initial admission. Uns...

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