AIMC Topic: Humans

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Deep Learning Approach for Anterior Cruciate Ligament Lesion Detection: Evaluation of Diagnostic Performance Using Arthroscopy as the Reference Standard.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: MRI is the most commonly used imaging method for diagnosing anterior cruciate ligament (ACL) injuries. However, the interpretation of knee MRI is time-intensive and depends on the clinical experience of the reader. An automated detection ...

A Deep Learning-Based Tumor Classifier Directly Using MS Raw Data.

Proteomics
Since the launch of Chinese Human Proteome Project (CNHPP) and Clinical Proteomic Tumor Analysis Consortium (CPTAC), large-scale mass spectrometry (MS) based proteomic profiling of different kinds of human tumor samples have provided huge amount of v...

Prediction of 1-Year Mortality from Acute Myocardial Infarction Using Machine Learning.

The American journal of cardiology
Risk stratification at hospital discharge could be instrumental in guiding postdischarge care. In this study, the risk models for 1-year mortality using machine learning (ML) were evaluated for guiding management of acute myocardial infarction (AMI) ...

An automated detection system for colonoscopy images using a dual encoder-decoder model.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Conventional computer-aided detection systems (CADs) for colonoscopic images utilize shape, texture, or temporal information to detect polyps, so they have limited sensitivity and specificity. This study proposes a method to extract possible polyp fe...

Left ventricle quantification with sample-level confidence estimation via Bayesian neural network.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Quantification of cardiac left ventricle has become a hot topic due to its great significance in clinical practice. Many efforts have been devoted to LV quantification and obtained promising performance with the help of various deep neural networks w...

The good, the bad, and the ugly in chemical and biological data for machine learning.

Drug discovery today. Technologies
Machine learning and artificial intelligence (ML/AI) have become important research tools in molecular medicine and chemistry. Their rise and recent success in drug discovery promises a rapid progression of development pipelines while reshaping how f...

Prediction of treatment effect perception in cosmetics using machine learning.

Journal of biopharmaceutical statistics
Perception of treatment effect (TE) in cosmetics is multifaceted and influenced by multiple parameters that need to be considered simultaneously when evaluating TE. Here we provide a global approach to predicting TE perception using Random Forest (RF...

An intelligent way for discerning plastics at the shorelines and the seas.

Environmental science and pollution research international
Irrespective of how plastics litter the coastline or enter the sea, they pose a major threat to birds and marine life alike. In this study, an artificial intelligence tool was used to create an image classifier based on a convolutional neural network...

Three-Dimensional Neural Network to Automatically Assess Liver Tumor Burden Change on Consecutive Liver MRIs.

Journal of the American College of Radiology : JACR
BACKGROUND: Tumor response to therapy is often assessed by measuring change in liver lesion size between consecutive MRIs. However, these evaluations are both tedious and time-consuming for clinical radiologists.