AI Medical Compendium

KRASG12V/A146T mutations are associated with nCRT resistance via enhanced DNA double-strand break repair and support a deep learning prediction framework in LARC.

Cellular & molecular biology letters May 28, 2026

BACKGROUND: Neoadjuvant chemoradiotherapy (nCRT) is the standard treatment for locally advanced rectal cancer (LARC), yet clinically validated biomarkers for predicting response remain lacking. This study aimed to identify candidate molecular events ... read more

AutoCumulus: an automated mammographic density measure created using artificial intelligence.

BMC cancer May 28, 2026

BACKGROUND: Mammographic (or breast) density is an established risk factor for breast cancer, previously measured using a variety of quantitative, semi-automated and automated approaches. We present a new automated measure, AutoCumulus, learned from ... read more

Deep learning for early detection of guava fruit anthracnose and fruit fly infestation.

BMC plant biology May 28, 2026

Anthracnose and fruit fly infestation are major biotic constraints on guava (Psidium guajava) production in South Asia, causing substantial yield losses and post-harvest degradation. Early-stage symptoms (lesions < 2 mm, subtle puncture marks) are of... read more

Joint trajectories of sleep duration and depressive symptoms and risk of incident multimorbidity: a longitudinal analysis with machine learning prediction.

BMC geriatrics May 28, 2026

BACKGROUND: Sleep disturbances and depressive symptoms frequently co-occur in older adults. Both conditions follow distinct, time-varying trajectories. Nevertheless, most studies rely on cross-sectional assessments, limiting evidence regarding their ... read more

A multi-sequence MRI integration framework using SwinUNETR-v2 for multiple sclerosis lesion segmentation.

BMC medical informatics and decision making May 28, 2026

Multiple Sclerosis (MS) is a chronic brain disease that affects the brain and spinal cord, where Magnetic Resonance Imaging (MRI) plays a key role in diagnosis. While manual analysis of brain MRIs is important, it is time-consuming and prone to human... read more

Demographic prompt cues shift clinical recommendations in multimodal large language models: a multi-model audit of 25,380 dental radiograph assessments.

BMC oral health May 28, 2026

BACKGROUND: Multimodal large language models (LLMs) are increasingly being evaluated for clinical image interpretation, but whether patient demographic cues influence their recommendations remains unclear in dental radiology-a leading domain for AI-a... read more

Machine learning for postoperative complication prediction and early recurrence risk assessment across cancer types: a systematic review and meta-analysis.

Cancer cell international May 28, 2026

BACKGROUND: Although machine learning is often used in medical diagnosis, its effectiveness in cancer diagnosis remains uncertain. OBJECTIVE: To explore the ability of machine learning to predict cancer postoperative complications and early recurrenc... read more

Machine learning and natural language processing for the identification of potential mental disorders among school-age children: a prospective birth cohort study.

BMC medicine May 28, 2026

BACKGROUND: Early identification of childhood mental health disorders is a critical public health objective. Existing screening approaches, largely dependent on observer reports, are resource-intensive and may overlook subtle internalized symptoms. T... read more

Identifying necessary conditions for medical students' adoption of AI in the future practice: a survey study in Canada.

BMC medical education May 28, 2026

BACKGROUND: As artificial intelligence (AI) technologies become increasingly embedded in healthcare, the readiness of future physicians to adopt these tools is of growing concern. While prior studies have examined predictors of technology acceptance,... read more

Cardiac arrhythmia detection via PQRST analyzed data using an optimized hierarchical fused fuzzy deep reinforcement learning.