AI Medical Compendium

MicroRNAs in endometriosis: bioinformatics resources, machine learning strategies, and multi-omics perspectives.

Journal of translational medicine May 25, 2026

BACKGROUND: Endometriosis is a heterogeneous gynecological disorder characterized by chronic pain, infertility, and substantial impairment of quality of life. Increasing evidence indicates that microRNAs (miRNAs) are key regulators of endometriosis p... read more

A hybrid cluster-then-predict machine learning radiotherapy knowledge-based planning framework for similarity matching using holistic target-OAR constellation geometry.

Radiation oncology (London, England) May 25, 2026

PURPOSE: Radiotherapy treatment planning is currently premised on individual clinical experience and use of many dose based optimization and knowledge-based planning (KBP) models. This study introduces and validates a novel KBP algorithm that matches... read more

Predicting fire consequences with the transformer model based on multimodal feature fusion.

Journal of cheminformatics May 25, 2026

Accurate prediction of fire consequences is fundamental to process safety management and quantitative risk assessment in the chemical process industries. Traditional empirical and computational fluid dynamics models often struggle to balance computat... read more

Evaluating Injection Laryngoplasty Skills Using a Foundation Model: A Feasibility Study.

The Laryngoscope May 25, 2026

OBJECTIVES: To evaluate the construct validity of a commercially available multimodal foundation model (Google Gemini 2.5 Pro) in assessing simulated injection laryngoplasty. METHODS: Thirty video recordings of simulated injection laryngoplasty proce... read more

Machine learning-based preoperative classification of colorectal cancer stage using systemic inflammatory and nutritional biomarkers.

BMC gastroenterology May 25, 2026

BACKGROUND: Accurate preoperative staging in colorectal cancer (CRC) is critical for determining the appropriate treatment strategy. This study evaluated whether early-stage (TNM I-II) and advanced-stage (TNM III-IV) CRC could be distinguished using ... read more

Evaluating the performance of ChatGPT in responding to myotonic dystrophy type 1 patient inquiries: a specialist physician-based study.

BMC neurology May 25, 2026

BACKGROUND: Advancements in artificial intelligence have led to the widespread use of large language models such as ChatGPT in healthcare communication. Myotonic dystrophy type 1, a chronic and multisystemic neuromuscular disorder, poses significant ... read more

Leveraging the non-contrast CT component of PET/CT: an AI-driven delta-radiomics approach to monitor treatment response in metastatic breast cancer.

BMC medical imaging May 25, 2026

PURPOSE: 18 F-FDG PET/CT is the standard modality for monitoring treatment response in metastatic breast cancer. This study aims to evaluate the predictive value of delta-radiomics derived solely from the low-dose, non-contrast CT component acquired ... read more

Spatial synergy in the digital era: a geo-analytics framework for detecting regional health patterns in urban smart city development.

BMC public health May 25, 2026

BACKGROUND: With enhanced digitization of large-scale health and socio-economic data, it has generated new opportunities and challenges in the processes and planning of smart cities in the cities and public health. It is increasingly becoming necessa... read more

Artificial intelligence for brain-to-speech decoding in paralysis: a systematic review.

BMC medical informatics and decision making May 25, 2026

The loss of communication constitutes a critical challenge for people living with paralysis. Brain-computer interfaces (BCIs) paired with artificial intelligence (AI) provide an opportunity to restore this ability. This systematic review examined the... read more

Predicting stride time variability from waist-mounted IMU data using machine learning: toward non-invasive gait stability monitoring in endurance running.

BMC sports science, medicine & rehabilitation May 25, 2026

BACKGROUND: Stride time variability (STV) is an important indicator of gait stability and motor control during running, yet its assessment typically depends on laboratory-based systems or distal sensor placement. This study evaluated whether a single... read more

Artificial Intelligence Medical Compendium