AIMC Topic: Machine Learning

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Microaneurysm Detection Using Principal Component Analysis and Machine Learning Methods.

IEEE transactions on nanobioscience
Diabetic retinopathy (DR) is an eye abnormality caused by long-term diabetes and it is the most common cause of blindness before the age of 50. Microaneurysms (MAs), resulting from leakage from retinal blood vessels, are early indicators of DR. In th...

A Novel Method to Predict Knee Osteoarthritis Progression on MRI Using Machine Learning Methods.

IEEE transactions on nanobioscience
This paper explored the hidden biomedical information from knee magnetic resonance (MR) images for osteoarthritis (OA) prediction. We have computed the cartilage damage index (CDI) information from 36 informative locations on tibiofemoral cartilage c...

Tracking antibiotic resistance gene pollution from different sources using machine-learning classification.

Microbiome
BACKGROUND: Antimicrobial resistance (AMR) has been a worldwide public health concern. Current widespread AMR pollution has posed a big challenge in accurately disentangling source-sink relationship, which has been further confounded by point and non...

Concussion classification via deep learning using whole-brain white matter fiber strains.

PloS one
Developing an accurate and reliable injury predictor is central to the biomechanical studies of traumatic brain injury. State-of-the-art efforts continue to rely on empirical, scalar metrics based on kinematics or model-estimated tissue responses exp...

Using Machine Learning to Advance Personality Assessment and Theory.

Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc
Machine learning has led to important advances in society. One of the most exciting applications of machine learning in psychological science has been the development of assessment tools that can powerfully predict human behavior and personality trai...

Computer-assisted liver graft steatosis assessment via learning-based texture analysis.

International journal of computer assisted radiology and surgery
PURPOSE: Fast and accurate graft hepatic steatosis (HS) assessment is of primary importance for lowering liver dysfunction risks after transplantation. Histopathological analysis of biopsied liver is the gold standard for assessing HS, despite being ...

Sarcopenia: Beyond Muscle Atrophy and into the New Frontiers of Opportunistic Imaging, Precision Medicine, and Machine Learning.

Seminars in musculoskeletal radiology
As populations continue to age worldwide, the impact of sarcopenia on public health will continue to grow. The clinically relevant and increasingly common diagnosis of sarcopenia is at the confluence of three tectonic shifts in medicine: opportunisti...

Automated chest screening based on a hybrid model of transfer learning and convolutional sparse denoising autoencoder.

Biomedical engineering online
OBJECTIVE: In this paper, we aim to investigate the effect of computer-aided triage system, which is implemented for the health checkup of lung lesions involving tens of thousands of chest X-rays (CXRs) that are required for diagnosis. Therefore, hig...

Machine learning in the integration of simple variables for identifying patients with myocardial ischemia.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: A significant number of variables are obtained when characterizing patients suspected with myocardial ischemia or at risk of MACE. Guidelines typically use a handful of them to support further workup or therapeutic decisions. However, it ...