AIMC Topic: Machine Learning

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SCREEN-DR: Collaborative platform for diabetic retinopathy.

International journal of medical informatics
BACKGROUND AND OBJECTIVE: Diabetic retinopathy (DR) is the most prevalent microvascular complication of diabetes mellitus and can lead to irreversible visual loss. Screening programs, based on retinal imaging techniques, are fundamental to detect the...

Machine Meets Biology: a Primer on Artificial Intelligence in Cardiology and Cardiac Imaging.

Current cardiology reports
PURPOSE OF REVIEW: An understanding of the basics concepts of deep learning can be helpful in not only understanding the potential applications of this technique but also in critically reviewing literature in which neural networks are utilized for an...

ECG Signal Classification Using Various Machine Learning Techniques.

Journal of medical systems
Electrocardiogram (ECG) signal is a process that records the heart rate by using electrodes and detects small electrical changes for each heat rate. It is used to investigate some types of abnormal heart function including arrhythmias and conduction ...

Modeling of stem form and volume through machine learning.

Anais da Academia Brasileira de Ciencias
Taper functions and volume equations are essential for estimation of the individual volume, which have consolidated theory. On the other hand, mathematical innovation is dynamic, and may improve the forestry modeling. The objective was analyzing the ...

Machine learning to support social media empowered patients in cancer care and cancer treatment decisions.

PloS one
BACKGROUND: A primary variant of social media, online support groups (OSG) extend beyond the standard definition to incorporate a dimension of advice, support and guidance for patients. OSG are complementary, yet significant adjunct to patient journe...

Psychiatric stressor recognition from clinical notes to reveal association with suicide.

Health informatics journal
Suicide takes the lives of nearly a million people each year and it is a tremendous economic burden globally. One important type of suicide risk factor is psychiatric stress. Prior studies mainly use survey data to investigate the association between...

Drug Repurposing Prediction for Immune-Mediated Cutaneous Diseases using a Word-Embedding-Based Machine Learning Approach.

The Journal of investigative dermatology
Immune-mediated diseases affect more than 20% of the population, and many autoimmune diseases affect the skin. Drug repurposing (or repositioning) is a cost-effective approach for finding drugs that can be used to treat diseases for which they are cu...

State of the Art: Machine Learning Applications in Glioma Imaging.

AJR. American journal of roentgenology
OBJECTIVE: Machine learning has recently gained considerable attention because of promising results for a wide range of radiology applications. Here we review recent work using machine learning in brain tumor imaging, specifically segmentation and MR...

Peering Into the Black Box of Artificial Intelligence: Evaluation Metrics of Machine Learning Methods.

AJR. American journal of roentgenology
OBJECTIVE: Machine learning (ML) and artificial intelligence (AI) are rapidly becoming the most talked about and controversial topics in radiology and medicine. Over the past few years, the numbers of ML- or AI-focused studies in the literature have ...

Machine learning-based phenogrouping in heart failure to identify responders to cardiac resynchronization therapy.

European journal of heart failure
AIMS: We tested the hypothesis that a machine learning (ML) algorithm utilizing both complex echocardiographic data and clinical parameters could be used to phenogroup a heart failure (HF) cohort and identify patients with beneficial response to card...