Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 53,951 to 53,960 of 225,930 articles

Global Quantification of Black Carbon in Seasonal Snow: A Physically and Observationally Constrained Machine-Learning Framework.

Environmental science & technology
Black carbon in seasonal snow (BCS) critically influences the Earth system by reducing surface albedo (snow darkening), perturbing radiative balance, and accelerating snowmelt. However, its climatic and hydrological impacts remain poorly quantified b... read more 

Association of urinary heavy metals with osteoporosis in US adults using interpretable machine learning.

Toxicology letters
BACKGROUND: Exposure to heavy metals in the environment has always been the focus of public concern. More and more evidence suggests that heavy metal exposure may lead to bone degeneration and an increased risk of pathological fractures. In this stud... read more 

Prediction models for maltreatment risk: TRIPOD/PROBAST compliance, calibration, and fairness-A systematic review.

Child abuse & neglect
BACKGROUND: Prediction models for child maltreatment risk are increasingly used to support decisions in child protection, yet concerns remain about methodological quality, transparency, calibration, and equity, particularly when tools are derived fro... read more 

Prioritising clinical feasibility and practicality in machine learning-based prediction model: Author's reply.

Australian critical care : official journal of the Confederation of Australian Critical Care Nurses
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Internal validation of the French Attitudes toward AI in Defense (AAID) scale: Evidence from an open dataset.

Acta psychologica
Artificial Intelligence (AI) is becoming a central strategic concern for military powers. Understanding public attitudes toward its use in defense may be critical for predicting acceptance or rejection, underscoring the need for validated assessment ... read more 

The application of artificial intelligence in cryopreservation: Technological advances and future challenges.

Cryobiology
This review systematically sorts out the latest research progress and application status of artificial intelligence (AI) technology in the field of cryopreservation, with a focus on its action mechanisms in aspects such as protocol optimization, dama... read more 

A comparative analysis of secondary unilateral and bilateral cleft lip nasal deformities: From anatomical characteristics to repair strategies.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Secondary cleft lip nasal deformity presents a persistent challenge in reconstructive surgery, with fundamental differences existing between unilateral and bilateral presentations that dictate distinct management approaches. This systematic review de... read more 

Understanding public perceptions of cultural ecosystem services in urban coastal wetland ecological restoration areas: A social media-based large language model approach.

Journal of environmental management
Understanding public perceptions of cultural ecosystem services (CES) in urban coastal wetland ecological restoration areas was essential for coastal resource management and sustainable development. Although social media data has been increasingly ut... read more 

Board gender diversity and emissions performance: Insights from panel regressions, machine learning, and explainable AI.

Journal of environmental management
With European Union initiatives mandating gender quotas on corporate boards, a key question arises: Is greater board gender diversity (BGD) associated with better emissions performance (EP)? To answer this question, we examine the influence of BGD on... read more 

Physiological data-driven models for motion sickness prediction.

Applied ergonomics
With advances in autonomous vehicle technology and in-cabin occupant monitoring systems, prediction of motion sickness (MS) has emerged as a key challenge to improve passenger experience. In this paper, a framework for MS prediction is proposed lever... read more