Geriatrics

Combining EEG, event-related potentials, and MRI biomarkers for detection of mild cognitive impairment: A machine learning approach.

OBJECTIVE: Mild cognitive impairment (MCI) is an intermediary stage between typical cognitive aging and dementia. Identifying reliable biomarkers for early detection of MCI is crucial for slowing disease progression. This study explored multimodal biomarkers associated with amyloid-positive MCI and assessed wearable EEG/ERP and MRI features using machine learning. METHODS: This study included 70 p...

Design and implementation of an end-to-end AI-driven colonoscopy recall workflow at scale.

OBJECTIVES: To develop a large-language-model (LLM)-centric workflow flow extraction and migration of clinician-documented colonoscopy recall recommendations from unstructured reports and letters during an enterprise-wide electronic health record (EHR) transition. MATERIALS AND METHODS: A multi-stage workflow [Optical Character Recognition (OCR) -> LLM -> structured fields] was built around a cent...

Developing and Internally Validating AI-Based Aging Resilience Biomarkers in Non-Human Primates.

Quantifying biological aging is crucial for understanding functional decline before the onset of morbidity. While many accelerated aging and frailty m...

Large language models for deductive qualitative content analysis in dementia-focused embedded pragmatic clinical trials: A comparative methodological study.

INTRODUCTION: Thematic coding helps researchers characterize intervention implementation in embedded pragmatic clinical trials (ePCTs), particularly i...

Ethical Assessment of Generative AI Tools for Clinical Summarization Tasks.

As healthcare organizations' use of generative AI moves from initial experimentation to scaled deployments, the need to build oversight systems to ide...

Deep Learning Algorithms Versus Radiologists in Digital Breast Tomosynthesis for Breast Cancer Detection: Systematic Review and Meta-Analysis.

BACKGROUND: Deep learning (DL) algorithms for digital breast tomosynthesis (DBT) have proliferated, demonstrating emerging potential in enhancing lesi...

Factors Associated with Respite Care Use Among Veteran Caregivers: A Machine Learning Analysis.

BACKGROUND AND OBJECTIVES: Respite care provides temporary relief to family caregivers yet remains underused, and the factors shaping its utilization ...

Machine learning-based information flow analysis of ECG signals for long QT syndrome.

Cardiovascular diseases remain the leading cause of death worldwide, highlighting the need for non-invasive and cost-effective risk assessment tools. ...

An intelligent auxiliary diagnostic system for early osteoporosis screening using stacking ensemble learning.

Robust disease prognosis via diagnostic knowledge preservation: A sequential learning approach.

Accurate disease prognosis is essential for patient care but is often hindered by the scarcity of longitudinal data. This study explores deep learning...

The presymptomatic and early manifestations of semantic dementia.

People with semantic dementia (SD) or semantic variant primary progressive aphasia typically present with marked atrophy of the anterior temporal lobe...

Artificial intelligence in nutritional assessment and decision making.

PURPOSE OF THE REVIEW: Artificial intelligence (AI) has become an non contourable tool in clinical nutrition practice. This review proposes to discuss...

An epidemiological study of Parkinson's disease in Chinese older adults using the Global Burden of Disease and China Health and Retirement Longitudinal Study databases.

INTRODUCTION: The prevalence of Parkinson's disease (PD) has increased globally, especially in China, and emerged as a critical public health challeng...

The utilization of Artificial Intelligence-based conversational agents on mental health care for older adults: a scoping review.

OBJECTIVES: Conversational Agents (CAs), commonly referred to as chatbots, are increasingly employed in mental health care, with applications ranging ...

AI and network biology for rational polypharmacology in signaling drug design: a review.

The complexity of disease-causing signaling networks is indicative of the failure of single-target therapeutics to work, particularly because of feedb...

Executive summary of the 2026 consensus document. Planning the future of Internal Medicine: A position statement of the International Forum of Internal Medicine (FIMI).

The International Forum of Internal Medicine (FIMI) presents a position paper that analyzes the current state and projects the future of Internal Medi...

Development and validation of a risk stratification model for sarcopenia in patients with chronic lung disease: a cross-sectional study based on CHARLS data.

OBJECTIVE: The aim of this study was to develop a machine learning-based stratification model to identify high-risk individuals for sarcopenia among p...

Machine learning predicts postoperative mortality in a Latin American cardiovascular surgery multicenter cohort: Toward precision risk stratification.

OBJECTIVE: A total of 28% of global cardiac surgeries are performed in Latin America; however, surgeons there are faced with many preventable deaths, ...

Data-driven detection of lucid episodes in advanced dementia: Application of latent class analysis to observational data.

BackgroundLucid episodes (LEs) in advanced dementia are significant clinical events yet are challenging to investigate as they are characterized by a ...

Investigating the Implementation and Impact of AI-Assisted Fall Prevention in Hospitals: Protocol for a Multicenter, Multimethod Observational Study in Sweden (SAFE).

BACKGROUND: Artificial intelligence (AI) has the potential to enhance patient safety, particularly in the prevention of in-hospital falls. Recent adva...