AIMC Topic: Male

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Machine learning identification of tinnitus-related features in auditory peripheral spontaneous activity in a guinea pig noise-induced tinnitus model.

Hearing research
OBJECTIVES: Tinnitus affects millions globally, yet its clinical assessment relies on subjective reports, limiting diagnostic accuracy and treatment development. This study aimed to identify objective, tinnitus-related features within ensemble sponta...

Multimodal neuroimaging unveils basal forebrain-limbic system circuit dysregulation in cognitive impairment with depression: a pathway to early diagnosis and intervention.

The journal of prevention of Alzheimer's disease
BACKGROUND: Alzheimer's disease (AD) frequently co-occurs with depressive symptoms, exacerbating both cognitive decline and clinical complexity, yet the neural substrates linking this co-occurrence remain poorly understood. We aimed to investigate th...

Developing the CAM-BERT: Enhancing delirium screening in hospitalized older adults using natural language processing.

Computers in biology and medicine
BACKGROUND: Delirium is a common condition affecting hospitalized older adults, often leading to adverse outcomes. Nevertheless, delirium frequently goes unrecognized due to various clinical and systemic challenges. We aimed to develop and evaluate a...

Comparison of synthetic LGE with optimal inversion time vs. conventional LGE via representation learning: Quantification of Bias in Population Analysis.

Computers in biology and medicine
PURPOSE: Late Gadolinium Enhancement (LGE) images are crucial elements of CMR protocols for evaluating myocardial infarct (MI) severity and size. However, these images rely on signal intensity changes and manual inversion time (TI) settings, leading ...

Beyond traditional models: Jaya-optimized ensembles for accurate heart disease prediction.

Computers in biology and medicine
INTRODUCTION: Heart Disease (HD) stands as the foremost reason for mortality all over the world for both men and women. Millions of people are affected worldwide every year, resulting in numerous fatalities. Timely and precise detection is essential ...

Machine Learning Prediction of Financial Toxicity in Patients with Resected Lung Cancer.

Journal of the American College of Surgeons
BACKGROUND: Financial toxicity (FT) refers to the financial stress and detrimental impact on quality of life experienced by patients due to treatment cost. In patients with resected lung cancer (LC), we sought to identify those at risk of developing ...

Which explanations do clinicians prefer? A comparative evaluation of XAI understandability and actionability in predicting the need for hospitalization.

BMC medical informatics and decision making
BACKGROUND: This study aims to address the gap in understanding clinicians' attitudes toward explainable AI (XAI) methods applied to machine learning models using tabular data, commonly found in clinical settings. It specifically explores clinicians'...

Knowledge and perception of artificial lntelligence education among undergraduate healthcare students.

BMC medical education
BACKGROUND: Artificial intelligence (AI) is gaining recognition for its ability to enhance patient outcomes in healthcare. Therefore, integrating AI into the undergraduate curriculum is essential to equip students with foundational knowledge before g...

Conditional GAN performs better than orthopedic surgeon in virtual reduction of femoral neck fracture.

BMC musculoskeletal disorders
OBJECTIVE: Satisfied reduction of fracture is hard to achieve. The purpose of this study is to develop a virtual fracture reduction technique using conditional GAN (Generative Adversarial Network), and evaluate its performance in simulating and guidi...

Development and evaluation of a deep learning-based system for dental age estimation using the demirjian method on panoramic radiographs.

BMC oral health
BACKGROUND: To develop and evaluate a deep learning-based model for automatic dental age estimation using the Demirjian method on panoramic radiographs, and to compare its performance with the traditional manual approach.