AIMC Topic: Male

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Using Wearable Device and Machine Learning to Predict Mood Symptoms in Bipolar Disorder: Development and Usability Study.

JMIR medical informatics
BACKGROUND: Bipolar disorder (BD) is a highly recurrent disorder. Early detection, early intervention, and prevention of recurrent bipolar mood symptoms are key to a better prognosis.

Development of a Data-Based Method for Predicting Nursing Workload in an Acute Care Hospital: Methodological Study.

Journal of medical Internet research
BACKGROUND: Determining effective nurse staffing levels is crucial for ensuring quality patient care and operational efficiency within hospitals. Traditional workload prediction methods often rely on professional judgment or simple volume-based appro...

Real-Time Estimation of Arterial Partial Pressure of Carbon Dioxide in Patients Undergoing General Anesthesia: Predictive Modeling Study.

JMIR medical informatics
BACKGROUND: Adequate ventilation in mechanically ventilated patients is contingent upon the monitoring of the arterial partial pressure of carbon dioxide (PaCO2) during general anesthesia. Despite its significance, continuous monitoring remains chall...

Submovements Derived from Wearable Sensors Capture Ataxia Severity and Differ Across Motor Tasks and Directions of Motion.

Cerebellum (London, England)
Digital measures derived from wearable sensors are a promising approach for assessing motor impairment in clinical trials. Submovements, which are velocity curves extracted from time series data, have been successful in characterizing impaired moveme...

Clinical validation of a deep learning based application for quantitative assessment of dental plaque in fluorescence imaging.

Clinical oral investigations
AIM: Evaluating dental plaque is a fundamental task for periodontal health care, but it is subjective, time-consuming, and cumbersome. Therefore, this study aimed to develop and validate a web-based deep learning application capable of objectively qu...

Novel and optimized mouse behavior enabled by fully autonomous HABITS: Home-cage assisted behavioral innovation and testing system.

eLife
Mice are among the most prevalent animal models used in neuroscience, benefiting from the extensive physiological, imaging, and genetic tools available to study their brain. However, the development of novel and optimized behavioral paradigms for mic...

Development of a predictive model for distant metastasis in HCC patients post-TACE using clinical data, radiomics, and deep learning.

Journal of cancer research and clinical oncology
PURPOSE: Hepatocellular carcinoma (HCC) is a perilous malignant tumor, and transcatheter arterial chemoembolization (TACE) is a widely adopted treatment technique for advanced HCC. Nevertheless, TACE may not effectively reduce the risk of distant met...

Development of a prostate cancer biochemical recurrence risk signature using machine learning and motor protein-related genes.

PloS one
BACKGROUND: Motor proteins play significant roles in cancer progression, but their involvement in biochemical recurrence (BCR) of prostate cancer remains unclear. The objective of the study is to develop a prognostic indicator for BCR using machine l...

A deep learning approach to gender equality: Forecasting educational indicators with 1D-CNN aligned with SDG 5.

PloS one
Sustainable development goal (SDG) 5 focuses on gender equality and empowerment and it is considered as one of the most important SDGs. Therefore, this article presented a time series prediction model that predicts gender-related educational results ...

Liquiritin in Chaihu-shugan-san alleviates Parkinson's Disease via PPARα-mediated inhibition of SCD1/FADS2-dependent Ferroptosis.

Phytomedicine : international journal of phytotherapy and phytopharmacology
BACKGROUND: Parkinson's disease (PD) is a progressive neurodegenerative disorder with increasing global prevalence. Chaihu-shugan-san (CSS) is a Chinese medicine compound with reported neuroprotective properties. However, the precise bioactive consti...