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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...

Identifying in Palliative Care Consultations: A Tandem Machine-Learning and Human Coding Method.

Journal of palliative medicine
Systematic measurement of conversational features in the natural clinical setting is essential to better understand, disseminate, and incentivize high quality serious illness communication. Advances in machine-learning (ML) classification of human s...

Assistance Robotics and Biosensors.

Sensors (Basel, Switzerland)
This Special Issue is focused on breakthrough developments in the field of biosensors and current scientific progress in biomedical signal processing. The papers address innovative solutions in assistance robotics based on bioelectrical signals, incl...

Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review.

Journal of medical Internet research
BACKGROUND: State-of-the-art classifiers based on convolutional neural networks (CNNs) were shown to classify images of skin cancer on par with dermatologists and could enable lifesaving and fast diagnoses, even outside the hospital via installation ...

Learning SPECT detector angular response function with neural network for accelerating Monte-Carlo simulations.

Physics in medicine and biology
A method to speed up [Formula: see text] simulations of single photon emission computed tomography (SPECT) imaging is proposed. It uses an artificial neural network (ANN) to learn the angular response function (ARF) of a collimator-detector system. T...

[Hepatitis B and renal failure: prevalence and associated factors in National University Hospital Center of Cotonou].

The Pan African medical journal
INTRODUCTION: the association between the kidneys and hepatitis B is complex. This study aims to determine the prevalence and factors associated with renal disease in people living with hepatitis B virus (PLHBV) in Cotonou.

Cosine Similarity Measure between Hybrid Intuitionistic Fuzzy Sets and Its Application in Medical Diagnosis.

Computational and mathematical methods in medicine
In this paper, a cosine similarity measure between hybrid intuitionistic fuzzy sets is proposed. The aim of the paper is to investigate the cosine similarity measure with hybrid intuitionistic fuzzy information and apply it to medical diagnosis. Firs...

Information-Based Boundary Equilibrium Generative Adversarial Networks with Interpretable Representation Learning.

Computational intelligence and neuroscience
This paper describes a new image generation algorithm based on generative adversarial network. With an information-theoretic extension to the autoencoder-based discriminator, this new algorithm is able to learn interpretable representations from the ...

Big data and targeted machine learning in action to assist medical decision in the ICU.

Anaesthesia, critical care & pain medicine
Historically, personalised medicine has been synonymous with pharmacogenomics and oncology. We argue for a new framework for personalised medicine analytics that capitalises on more detailed patient-level data and leverages recent advances in causal ...