AI Medical Compendium

Artificial intelligence-assisted polyp detection in colonoscopy - Methodological considerations for annotation standardization.

Journal of the Formosan Medical Association = Taiwan yi zhi Mar 17, 2026

Managing maternity: Moving care, not patients, using artificial intelligence (AI), internet-of-things (IOT) and point-of-care testing (POCT) devices.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics Mar 17, 2026

The integration of artificial intelligence (AI) into healthcare is accelerating and maternity care is at a pivotal moment for the strategic implementation of these technologies. This article explores how AI-assisted women's health innovations, often ... read more

Predicting risk of Plasmodium vivax microscopy-detected episodes using serological markers in patients with Plasmodium falciparum malaria: a multi-country diagnostic performance evaluation.

The Journal of infectious diseases Mar 17, 2026

BACKGROUND: Plasmodium vivax presents a significant obstacle to malaria elimination due to its capacity to form dormant liver-stage hypnozoites that can cause relapses. Universal radical cure, which administers hypnozoite-targeting treatment to patie... read more

Volatile fingerprinting and interpretable machine learning for authenticating New Zealand monofloral honeys.

Food research international (Ottawa, Ont.) Mar 17, 2026

Authenticating monofloral honeys is essential for protecting premium markets and ensuring traceability. This study applied an integrated analytical and explainable machine-learning workflow to identify volatile biomarkers for four New Zealand monoflo... read more

Development and Validation of Machine Learning Model to Predict Refractory Septic Shock.

Shock (Augusta, Ga.) Mar 17, 2026

This study developed and validated a machine learning model to predict refractory septic shock in patients with sepsis admitted to a tertiary care center in India. Using an ambispective design, data from 1,008 adult intensive care unit patients were ... read more

Machine Learning Predicts ICU In-Hospital Mortality in Ards Patients Aged 80 and Above: A Multinational Multicenter Retrospective Study.

Shock (Augusta, Ga.) Mar 17, 2026

BACKGROUND: The present study aims to develop and validate an interpretable machine learning (ML) model based on a multicenter cohort, which is intended for predicting the mortality of acute respiratory distress syndrome patients aged over 80 years a... read more

Permutation-Invariant graph partitioning: How graph neural networks capture structural interactions?

Neural networks : the official journal of the International Neural Network Society Mar 17, 2026

Graph Neural Networks (GNNs) have paved the way for being a cornerstone in graph-related learning tasks. Yet, the ability of GNNs to capture structural interactions within graphs remains under-explored. In this work, we address this gap by drawing on... read more

LymphUs: A multicenter open-access database of lymph node ultrasound images in patients with papillary thyroid carcinoma for clinical and artificial intelligence research.

Data in brief Mar 17, 2026

Approximately 30-50% of Papillary thyroid carcinoma (PTC) patients develop cervical lymph nodes (LNs) metastasis, significantly increasing the risk of disease recurrence and impacting long-term outcomes. We introduced an open-access multicenter lymph... read more

Rapid detection of drug-resistant leukemia cell using an optofluidic chip and machine learning.

Analytica chimica acta Mar 17, 2026

BACKGROUND: Rapid detection of drug-resistant leukemia played a crucial role in formulating appropriate treatment plans for patients and improving their prognosis. In this research, an integrated optofluidic platform was developed to detect and analy... read more

Machine learning-based QSPR modeling for predicting the n-octanol/air partition coefficient of polybrominated diphenyl ethers.

iScience Mar 17, 2026

The n-octanol/air partition coefficient (K OA) governs the trans-media transport and exposure risk of polybrominated diphenyl ethers (PBDEs). This study utilizes a super learner ensemble-integrating random forest, support vector regression, and multi... read more

Artificial Intelligence Medical Compendium