AIMC Topic: Male

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Machine learning models in predicting viability after testicular torsion: a proof of concept study.

Pediatric surgery international
PURPOSE: Decision-making for orchiectomy following testicular torsion often relies on subjective clinical evaluations. This study investigates the efficacy of machine learning (ML) models in objectively predicting post-torsion testicular viability, a...

AI assisted triage of UK patients in mental health care services: a qualitative focus group study of patients' attitudes.

BMC psychiatry
BACKGROUND: The referral process between healthcare services can be complex, especially in psychiatry, leading to significant delays and 'hidden waiting lists'. Digital approaches may be helpful. The CHRONOSIG (CHRONOlogical SIGnature) project aims t...

Deep learning-based segmentation and density estimation of corneal nerves and dendritic cells from In Vivo confocal microscopy images.

Scientific reports
The purpose of this study was to compare manual assessment of corneal nerve fiber length (CNFL) and dendritic cell (DC) density with an automated assessment method utilizing deep learning segmentation to perform rule-based density estimation. Corneal...

Improving rectal tumor segmentation with anomaly fusion derived from anatomical inpainting: a multicenter study.

Scientific reports
Accurate rectal tumor segmentation using magnetic resonance imaging (MRI) is paramount for effective treatment planning. It allows for volumetric and other quantitative tumor assessments, potentially aiding in prognostication and treatment response e...

AI-MK: artificial intelligence for assessing and monitoring microbial keratitis.

BMJ open ophthalmology
BACKGROUND/AIMS: To evaluate the performance of an artificial intelligence (AI) model for detecting and monitoring microbial keratitis (MK) using anterior segment optical coherence tomography (AS-OCT).

Evaluating the Efficacy of AI-Based Interactive Assessments Using Large Language Models for Depression Screening: Development and Usability Study.

JMIR formative research
BACKGROUND: The evolution of language models, particularly large language models, has introduced transformative potential for psychological assessment, challenging traditional rating scale methods that have dominated clinical practice for over a cent...

Effects of Artificial Intelligence Recognition-Based Telerehabilitation on Exercise Capacity in Patients With Hypertension: Randomized Controlled Trial.

Journal of medical Internet research
BACKGROUND: Hypertension remains a major global health challenge, significantly increasing cardiovascular and all-cause mortality risks. While exercise therapy is effective, conventional approaches face limitations in accessibility and personalizatio...

Explainable AI for Predicting Mortality Risk in Metastatic Cancer: Retrospective Cohort Study Using the Memorial Sloan Kettering-Metastatic Dataset.

JMIR cancer
BACKGROUND: Metastatic cancer remains one of the leading causes of cancer-related mortality worldwide. Yet, the prediction of survivability in this population remains limited by heterogeneous clinical presentations and high-dimensional molecular feat...

Neutrophil Percentage-to-Albumin Ratio as a Novel Prognostic Biomarker in Adult Diffuse Gliomas: Retrospective Study Integrating 3 Machine Learning Models and Cox Regression.

JMIR medical informatics
BACKGROUND: Adult-type diffuse glioma (ADG) is the most common primary malignant tumor of the central nervous system. Its highly invasive nature, marked heterogeneity, and resistance to therapy contribute to a high risk of recurrence and poor prognos...

Development of an explainable prediction model for the risk of moderate-to-severe obstructive sleep apnea in children.

European journal of pediatrics
UNLABELLED: Early identification of children at high risk for moderate-to-severe obstructive sleep apnea (OSA) is crucial for timely intervention, yet is often hindered by limited access to polysomnography (PSG). We aimed to develop an interpretable ...