Artificial Intelligence Medical Compendium

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

Showing 8,671 to 8,680 of 208,216 articles

External Validation of a mHealth Tool for Detecting Gingival Inflammation in Community-Dwelling Older Adults.

Journal of dentistry
OBJECTIVE: This study aimed to externally validate the screening performance of a pro-social (equitable, accessible), explainable AI (XAI)-guided mobile health (mHealth) tool, GumAI, that automated the analysis of smartphone photographs to detect sig... read more 

Evaluation of two large language models for intensive care unit discharge decisions: a prospective observational cohort study.

Brazilian journal of anesthesiology (Elsevier)
BACKGROUND: The aim of this study was to evaluate the effectiveness of two general-purpose Large Language Models (LLMs), ChatGPT and Gemini, in predicting Intensive Care Unit (ICU) discharge decisions (discharge vs. non-discharge). By comparing their... read more 

Fluid-based biomarkers of amyotrophic lateral sclerosis: recent advances and future prospects.

Brain research
Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disorder with no definitive cure. The absence of specific diagnostic biomarkers leads to diagnostic delays, hindering early intervention and management. This review provides a cri... read more 

Automated dairy cattle body condition score using side-view images and deep learning.

Journal of dairy science
Body condition score (BCS) is key to assessing the health, productivity, and energy balance of dairy cows. However, traditional manual methods are time-intensive, dependent on evaluator experience, and prone to subjective biases, limiting large-scale... read more 

Development and validation of a serum microRNA biomarker panel for bovine Johne's disease.

Journal of dairy science
Johne's disease (JD) is a chronic wasting disease of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP). For decades, JD management has been hampered by the lack of a sensitive diagnostic test. Here we have developed a machine-... read more 

Image-driven in situ grading of compost maturity using deep feature clustering and supervised prediction.

Bioresource technology
Accurate and cost-effective grading of compost maturity is critical for agronomic safety and process optimization. This study developed an image-driven in situ grading framework for compost maturity using deep feature clustering and supervised predic... read more 

Achieving high-quality and safe compost: a study on multi-optimization of a non-linear system using machine learning.

Bioresource technology
Composting represents one of the most effective strategies for animal manure utilization, while its yield efficiency and product safety are constrained by critical bottlenecks including excess nutrient loss and persistence of hazardous residues. Ther... read more 

Deep Learning-Based Diagnosis of Parotid Gland Tumors on CT Images: A Multi-view Approach for Preoperative Differentiation of Benign and Malignant Lesions.

Journal of stomatology, oral and maxillofacial surgery
BACKGROUND: Accurate preoperative differentiation between benign and malignant parotid gland tumors is essential for guiding surgical planning and treatment decisions. However, early-stage malignant tumors often lack distinctive imaging features on c... read more 

Development and validation of a noninvasive machine learning model using urinary extracellular vesicle physical parameters for prostate cancer diagnosis.

Scientific reports
Urinary extracellular vesicles (uEVs) are promising biomarkers for prostate cancer (PCa). Although novel uEV-based biomarkers have advanced early diagnosis, their detection processes remain cumbersome and cost-prohibitive. The physical parameters of ... read more 

Authorship identification for Chinese literature based on a pyramid deep bidirectional gated recurrent unit network with voting strategy.

Scientific reports
Identifying the author of given textual excerpts is a challenging and significant task in computational linguistics. In this paper, we propose a novel deep-learning model structured based on a Pyramid Deep Bidirectional Gated Recurrent Unit (biGRU) n... read more