AI Medical Compendium

Integrating Taguchi design and machine learning models for trait stability and predicting forage quality in naturally occurring grass pea (Lathyrus spp.).

BMC plant biology May 20, 2026

This study investigated the forage quality of four naturally occurring Lathyrus species (Lathyrus czeczottianus, L. pratensis, L. roseus, and L. rotundifolius subsp. miniatus), including one endemic taxon, collected from the Rize province of Turkey. ... read more

Modeling and classifying neuronal activity with a fusion of mathematical and machine learning techniques.

BMC bioinformatics May 20, 2026

Predicting neuron spike patterns is crucial because spikes are the brain's fundamental language, revealing how information is encoded and transmitted. Such prediction also supports disease diagnosis, brain-machine interfaces, and the control of robot... read more

Identifying the factors influencing long-term care utilization by older adults in China: machine learning analysis.

BMC geriatrics May 20, 2026

BACKGROUND: To address the aging population in China, local governments began to encourage the establishment of formal care services and supplement informal care in 2015, thereby increasing the availability of different types of long-term care (LTC).... read more

Bridging ensemble model and public health practice: an approach for refining understanding of seasonal dengue transmission patterns in Bangladesh.

BMC infectious diseases May 20, 2026

BACKGROUND: Dengue fever remains a persistent public health threat in Dhaka, Bangladesh, necessitating effective early warning systems to enable timely interventions and mitigate impacts. This study develops and evaluates modeling approaches to produ... read more

Preoperative identification of tumor deposits in rectal cancer using a transformer-based multimodal fusion model: a multicenter retrospective study.

BMC medical imaging May 20, 2026

OBJECTIVE: To develop and validate a transformer-based deep learning-radiomics model for the non-invasive preoperative discrimination of tumor deposits (TDs) in rectal cancer by integrating multi-sequence MRI features and clinical risk factors. METHO... read more

Comparing the performance of statistical and machine learning survival models in predicting timing and determinants of postnatal care in Rwanda.

BMC pregnancy and childbirth May 20, 2026

BACKGROUND: Postnatal care (PNC) remains the least utilized component of the maternal care continuum despite its critical role in preventing maternal and neonatal deaths. Conventional survival models estimate associations and identify determinants of... read more

The impact of generative artificial intelligence on clinical skills and knowledge acquisition in medical undergraduates: a systematic review and meta-analysis.

BMC medical education May 20, 2026

BACKGROUND: Currently, there is a growing body of research examining the role of generative Artificial Intelligence (GenAI) in medical undergraduate education. However, the findings of these studies exhibit considerable variability. Therefore, this r... read more

Screening and diagnosis of combustion smoking with exhaled breath analysis via proton transfer reaction time-of-flight mass spectrometry.

BMC pulmonary medicine May 20, 2026

BACKGROUND: Tobacco smoking is a leading cause for lung cancer, even for non-smokers. Assessing exposure, particularly to passive or secondhand smoke, is challenging due to reliance on self-reporting and the invasiveness of traditional biomarker test... read more

An evidence-based nursing management app prototype for adult urology day surgery: an AI-driven development pathway.

BMC nursing May 20, 2026

OBJECTIVES: The nursing management of adult urology patients in day surgical settings has undergone rapid development. This study aimed to (1) retrieve, evaluate, and summarize the best available evidence regarding the perioperative nursing managemen... read more

A hybrid deep learning framework for accurate breast cancer classification using MRI images.

BMC medical informatics and decision making May 20, 2026

Early and accurate detection of breast cancer is crucial to enhance patient results, especially in high-risk populations where magnetic resonance imaging (MRI) is intensively used. This study shows a deep learning-based framework for the automatic cl... read more

Artificial Intelligence Medical Compendium