AIMC Topic:
Middle Aged

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Item Response Modeling and Artificial Neural Network for Differentiation of Parkinson's Patients and Subjects Without Evidence of Dopaminergic Deficit.

CPT: pharmacometrics & systems pharmacology
Approximately 15% of patients suspected of having Parkinson's disease (PD) present dopamine active transporter (DaT) scans without evidence of dopaminergic deficits (SWEDD), most of which will never develop PD. Leveraging Movement Disorders Society U...

Determining the Importance of Lifestyle Risk Factors in Predicting Binge Eating Disorder After Bariatric Surgery Using Machine Learning Models and Lifestyle Scores.

Obesity surgery
BACKGROUND: This study was conducted to assess the association between lifestyle risk factors (LRF) and odds of binge eating disorder (BED) 2 years post laparoscopic sleeve gastrectomy (LSG) using lifestyle score (LS) and machine learning (ML) models...

A machine learning approach to predict treatment efficacy and adverse effects in major depression using CYP2C19 and clinical-environmental predictors.

Psychiatric genetics
BACKGROUND: Major depressive disorder (MDD) is among the leading causes of disability worldwide and treatment efficacy is variable across patients. Polymorphisms in cytochrome P450 2C19 (CYP2C19) play a role in response and side effects to medication...

Predicting Readmission Among High-Risk Discharged Patients Using a Machine Learning Model With Nursing Data: Retrospective Study.

JMIR medical informatics
BACKGROUND: Unplanned readmissions increase unnecessary health care costs and reduce the quality of care. It is essential to plan the discharge care from the beginning of hospitalization to reduce the risk of readmission. Machine learning-based readm...

Investigating Whether AI Will Replace Human Physicians and Understanding the Interplay of the Source of Consultation, Health-Related Stigma, and Explanations of Diagnoses on Patients' Evaluations of Medical Consultations: Randomized Factorial Experiment.

Journal of medical Internet research
BACKGROUND: The increasing use of artificial intelligence (AI) in medical diagnosis and consultation promises benefits such as greater accuracy and efficiency. However, there is little evidence to systematically test whether the ideal technological p...

Deep learning for hepatocellular carcinoma recurrence before and after liver transplantation: a multicenter cohort study.

Scientific reports
Hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT) is a major contributor to mortality. We developed a recurrence prediction system for HCC patients before and after LT. Data from patients with HCC who underwent LT were retros...

Development and validation of automated three-dimensional convolutional neural network model for acute appendicitis diagnosis.

Scientific reports
Rapid, accurate preoperative imaging diagnostics of appendicitis are critical in surgical decisions of emergency care. This study developed a fully automated diagnostic framework using a 3D convolutional neural network (CNN) to identify appendicitis ...

Cold storage surpasses the impact of biological age and donor characteristics on red blood cell morphology classified by deep machine learning.

Scientific reports
Assessment of the morphology of red blood cells (RBCs) can improve clinical benefits following blood transfusion. Deep machine learning surpasses traditional microscopy-based classification methods, offering more accurate and consistent results while...

Separation of stroke from vestibular neuritis using the video head impulse test: machine learning models versus expert clinicians.

Journal of neurology
BACKGROUND: Acute vestibular syndrome usually represents either vestibular neuritis (VN), an innocuous viral illness, or posterior circulation stroke (PCS), a potentially life-threatening event. The video head impulse test (VHIT) is a quantitative me...

Assessing operative variability in robot-assisted radical prostatectomy (RARP) through AI.

Journal of robotic surgery
Robotic-assisted radical prostatectomy (RARP) is the most commonly performed robotic procedure in urology. Using artificial intelligence (AI), surgical steps and practices can be assessed and validated through surgical video, and connected to patient...