AIMC Topic: Male

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Development and validation of machine learning models for predicting venous thromboembolism in colorectal cancer patients: A cohort study in China.

International journal of medical informatics
BACKGROUND: With advancements in healthcare, traditional VTE risk assessment tools are increasingly insufficient to meet the demands of high-quality care, underscoring the need for innovative and specialized assessment methods.

Evaluating LLM-based generative AI tools in emergency triage: A comparative study of ChatGPT Plus, Copilot Pro, and triage nurses.

The American journal of emergency medicine
BACKGROUND: The number of emergency department (ED) visits has been on steady increase globally. Artificial Intelligence (AI) technologies, including Large Language Model (LLMs)-based generative AI models, have shown promise in improving triage accur...

A U-Net based partial convolutional time-domain separation model to identify motor units from surface electromyographic signals in real time.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
This study proposed a U-Net based partial convolutional time-domain model for a real-time high-density surface electromyography (HD-sEMG) decomposition. The model combines U-Net and a separation block containing partial convolution, aiming to efficie...

Prognostic models for progression-free survival in atypical meningioma: Comparison of machine learning-based approach and the COX model in an Asian multicenter study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Atypical meningiomas are prevalent intracranial tumors with varied prognoses and recurrence rates. The role of adjuvant radiotherapy (ART) in atypical meningiomas remains debated. This study aimed to develop and validate a pro...

Optimizing convolutional neural networks for Chronic Obstructive Pulmonary Disease detection in clinical computed tomography imaging.

Computers in biology and medicine
We aim to optimize the binary detection of Chronic Obstructive Pulmonary Disease (COPD) based on emphysema presence in the lung with convolutional neural networks (CNN) by exploring manually adjusted versus automated window-setting optimization (WSO)...

Automated detection of posterior urethral valves in voiding cystourethrography images: A novel AI-Based pipeline for enhanced diagnosis and classification.

Computers in biology and medicine
INTRODUCTION: Posterior Urethral Valves (PUV) are rare congenital anomalies of the male urinary tract that can lead to urethral obstruction and increased risk of kidney disease. Traditional diagnosis relies on subjective interpretation of imaging tec...

Comparative analysis of the human microbiome from four different regions of China and machine learning-based geographical inference.

mSphere
The human microbiome, the community of microorganisms that reside on and inside the human body, is critically important for health and disease. However, it is influenced by various factors and may vary among individuals residing in distinct geographi...

Digital phenotyping from wearables using AI characterizes psychiatric disorders and identifies genetic associations.

Cell
Psychiatric disorders are influenced by genetic and environmental factors. However, their study is hindered by limitations on precisely characterizing human behavior. New technologies such as wearable sensors show promise in surmounting these limitat...