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Development and validation comparison of multiple models for perioperative neurocognitive disorders during hip arthroplasty.

Scientific reports
This study aims to develop optimal predictive models for perioperative neurocognitive disorders (PND) in hip arthroplasty patients, thereby advancing clinical practice. Data from all hip arthroplasty patients in the MIMIC-IV database were utilized to...

Protocol for socioecological study of autism, suicide risk, and mental health care: Integrating machine learning and community consultation for suicide prevention.

PloS one
INTRODUCTION: Autistic people experience higher risk of suicidal ideation (SI) and suicide attempts (SA) compared to non-autistic people, yet there is limited understanding of complex, multilevel factors that drive this disparity. Further, determinan...

Neuro_DeFused-Net: A novel multi-scale 2DCNN architecture assisted diagnostic model for Parkinson's disease diagnosis using deep feature-level fusion of multi-site multi-modality neuroimaging data.

Computers in biology and medicine
BACKGROUND: Neurological disorders, particularly Parkinson's Disease (PD), are serious and progressive conditions that significantly impact patients' motor functions and overall quality of life. Accurate and timely diagnosis is still crucial, but it ...

Deep learning by Vision Transformer to classify bacterial and fungal keratitis using different types of anterior segment images.

Computers in biology and medicine
PURPOSE: To develop three novel Vision Transformer (ViT) frameworks for the specific diagnosis of bacterial and fungal keratitis using different types of anterior segment images and compare their performances.

Deep learning reconstruction for accelerated 3-D magnetic resonance cholangiopancreatography.

La Radiologia medica
PURPOSE: This study aimed to compare a conventional three-dimensional (3-D) magnetic resonance cholangiopancreatography (MRCP) sequence with a deep learning (DL)-accelerated MRCP sequence (hereafter, MRCP) regarding acquisition time and image quality...

User-Centered Prototype Design of a Health Care Robot for Treating Type 2 Diabetes in the Community Pharmacy: Development and Usability Study.

JMIR human factors
BACKGROUND: Technology can be an effective tool for providing health services and disease self-management, especially in diabetes care. Technology tools for disease self-management include health-related applications for computers and smartphones as ...

Predicting diabetic retinopathy based on routine laboratory tests by machine learning algorithms.

European journal of medical research
OBJECTIVES: This study aimed to identify risk factors for diabetic retinopathy (DR) and develop machine learning (ML)-based predictive models using routine laboratory data in patients with type 2 diabetes mellitus (T2DM).

Denoised recurrence label-based deep learning for prediction of postoperative recurrence risk and sorafenib response in HCC.

BMC medicine
BACKGROUND: Pathological images of hepatocellular carcinoma (HCC) contain abundant tumor information that can be used to stratify patients. However, the links between histology images and the treatment response have not been fully unveiled.

Does gender matter? The impact of gender and gender match on the relation between destructive leadership and follower outcomes.

BMC psychology
BACKGROUND: Destructive leadership has been linked to negative consequences for both organizations and followers. Research has also shown that leader gender affects follower perceptions of leadership behavior and follower outcomes [1-3]. However, kno...

Interpretable machine learning models for prolonged Emergency Department wait time prediction.

BMC health services research
OBJECTIVE: Prolonged Emergency Department (ED) wait times lead to diminished healthcare quality. Utilizing machine learning (ML) to predict patient wait times could aid in ED operational management. Our aim is to perform a comprehensive analysis of M...