AIMC Topic: Adult

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Deep-learning system for real-time differentiation between Crohn's disease, intestinal Behçet's disease, and intestinal tuberculosis.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Pattern analysis of big data can provide a superior direction for the clinical differentiation of diseases with similar endoscopic findings. This study aimed to develop a deep-learning algorithm that performs differential diagnosi...

Intrahepatic cholestasis of pregnancy: machine-learning algorithm to predict elevated bile acid based on clinical and laboratory data.

Archives of gynecology and obstetrics
PURPOSE: Applying machine-learning models to clinical and laboratory features of women with intrahepatic cholestasis of pregnancy (ICP) and creating algorithm to identify these patients without bile acid measurements.

Deep learning based automated diagnosis of bone metastases with SPECT thoracic bone images.

Scientific reports
SPECT nuclear medicine imaging is widely used for treating, diagnosing, evaluating and preventing various serious diseases. The automated classification of medical images is becoming increasingly important in developing computer-aided diagnosis syste...

A deep learning approach for lower back-pain risk prediction during manual lifting.

PloS one
Occupationally-induced back pain is a leading cause of reduced productivity in industry. Detecting when a worker is lifting incorrectly and at increased risk of back injury presents significant possible benefits. These include increased quality of li...

Performance of a deep-learning algorithm for referable thoracic abnormalities on chest radiographs: A multicenter study of a health screening cohort.

PloS one
PURPOSE: This study evaluated the performance of a commercially available deep-learning algorithm (DLA) (Insight CXR, Lunit, Seoul, South Korea) for referable thoracic abnormalities on chest X-ray (CXR) using a consecutively collected multicenter hea...

Early risk assessment for COVID-19 patients from emergency department data using machine learning.

Scientific reports
Since its emergence in late 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic with more than 55 million reported cases and 1.3 million estimated deaths worldwide. While epidemiological and clinical character...

FOPR test: a virtual reality-based technique to assess field of perception and field of regard in hemispatial neglect.

Journal of neuroengineering and rehabilitation
BACKGROUND: We previously proposed a novel virtual reality-based method to assess human field of perception (FOP) and field of regard (FOR), termed the FOPR test. This study assessed the diagnostic validity of the FOPR test for hemispatial neglect (H...

Correlation between lung infection severity and clinical laboratory indicators in patients with COVID-19: a cross-sectional study based on machine learning.

BMC infectious diseases
BACKGROUND: Coronavirus disease 2019 (COVID-19) has caused a global pandemic that has raised worldwide concern. This study aims to investigate the correlation between the extent of lung infection and relevant clinical laboratory testing indicators in...

Facial geometric feature extraction based emotional expression classification using machine learning algorithms.

PloS one
Emotion plays a significant role in interpersonal communication and also improving social life. In recent years, facial emotion recognition is highly adopted in developing human-computer interfaces (HCI) and humanoid robots. In this work, a triangula...

Artificial intelligence in outcomes research: a systematic scoping review.

Expert review of pharmacoeconomics & outcomes research
: Despite the number of systematic reviews of how artificial intelligence is being used in different areas of medicine, there is no study on the scope of artificial intelligence methods used in outcomes research, the cornerstone of health technology ...