AIMC Topic: Retrospective Studies

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Development and validation of radiomics model built by incorporating machine learning for identifying liver fibrosis and early-stage cirrhosis.

Chinese medical journal
BACKGROUND: Liver fibrosis (LF) continues to develop and eventually progresses to cirrhosis. However, LF and early-stage cirrhosis (ESC) can be reversed in some cases, while advanced cirrhosis is almost impossible to cure. Advances in quantitative im...

Using Artificial Intelligence to Measure Facial Expression following Facial Reanimation Surgery.

Plastic and reconstructive surgery
Social interactions are largely dependent on the interpretation of information conveyed through facial expressions. Although facial reanimation seeks restoration of the facial expression of emotion, outcome measures have not addressed this directly. ...

Validation of a Machine Learning Algorithm to Predict 180-Day Mortality for Outpatients With Cancer.

JAMA oncology
IMPORTANCE: Machine learning (ML) algorithms can identify patients with cancer at risk of short-term mortality to inform treatment and advance care planning. However, no ML mortality risk prediction algorithm has been prospectively validated in oncol...

An Explainable Artificial Intelligence Predictor for Early Detection of Sepsis.

Critical care medicine
OBJECTIVES: Early detection of sepsis is critical in clinical practice since each hour of delayed treatment has been associated with an increase in mortality due to irreversible organ damage. This study aimed to develop an explainable artificial inte...

Routine Laboratory Blood Tests Predict SARS-CoV-2 Infection Using Machine Learning.

Clinical chemistry
BACKGROUND: Accurate diagnostic strategies to identify SARS-CoV-2 positive individuals rapidly for management of patient care and protection of health care personnel are urgently needed. The predominant diagnostic test is viral RNA detection by RT-PC...

The Development and Validation of a Machine Learning Model to Predict Bacteremia and Fungemia in Hospitalized Patients Using Electronic Health Record Data.

Critical care medicine
OBJECTIVES: Bacteremia and fungemia can cause life-threatening illness with high mortality rates, which increase with delays in antimicrobial therapy. The objective of this study is to develop machine learning models to predict blood culture results ...

Is Deep Learning On Par with Human Observers for Detection of Radiographically Visible and Occult Fractures of the Scaphoid?

Clinical orthopaedics and related research
BACKGROUND: Preliminary experience suggests that deep learning algorithms are nearly as good as humans in detecting common, displaced, and relatively obvious fractures (such as, distal radius or hip fractures). However, it is not known whether this a...

Incidental cerebral aneurysms detected by a computer-assisted detection system based on artificial intelligence: A case series.

Medicine
RATIONALE: Computer-assisted detection (CAD) systems based on artificial intelligence (AI) using convolutional neural network (CNN) have been successfully used for the diagnosis of unruptured cerebral aneurysms in experimental situations. However, it...