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Quantifying influence of human choice on the automated detection of Drosophila behavior by a supervised machine learning algorithm.

PloS one
Automated quantification of behavior is increasingly prevalent in neuroscience research. Human judgments can influence machine-learning-based behavior classification at multiple steps in the process, for both supervised and unsupervised approaches. S...

A k-space-to-image reconstruction network for MRI using recurrent neural network.

Medical physics
PURPOSE: Reconstructing the images from undersampled k-space data are an ill-posed inverse problem. As a solution to this problem, we propose a method to reconstruct magnetic resonance (MR) images directly from k-space data using a recurrent neural n...

A review on medical imaging synthesis using deep learning and its clinical applications.

Journal of applied clinical medical physics
This paper reviewed the deep learning-based studies for medical imaging synthesis and its clinical application. Specifically, we summarized the recent developments of deep learning-based methods in inter- and intra-modality image synthesis by listing...

Detection of Hate Speech in COVID-19-Related Tweets in the Arab Region: Deep Learning and Topic Modeling Approach.

Journal of medical Internet research
BACKGROUND: The massive scale of social media platforms requires an automatic solution for detecting hate speech. These automatic solutions will help reduce the need for manual analysis of content. Most previous literature has cast the hate speech de...

Decoding semi-automated title-abstract screening: findings from a convenience sample of reviews.

Systematic reviews
BACKGROUND: We evaluated the benefits and risks of using the Abstrackr machine learning (ML) tool to semi-automate title-abstract screening and explored whether Abstrackr's predictions varied by review or study-level characteristics.

Design and rationale of an intelligent algorithm to detect BuRnoUt in HeaLthcare workers in COVID era using ECG and artificiaL intelligence: The BRUCEE-LI study.

Indian heart journal
BACKGROUND: There is no large contemporary data from India to see the prevalence of burnout in HCWs in covid era. Burnout and mental stress is associated with electrocardiographic changes detectable by artificial intelligence (AI).

Methodological considerations in MVC epidemiological research.

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
BACKGROUND: The global burden of MVC injuries and deaths among vulnerable road users, has led to the implementation of prevention programmes and policies at the local and national level. MVC epidemiological research is key to quantifying MVC burden, ...

Protocol for a systematic review on the methodological and reporting quality of prediction model studies using machine learning techniques.

BMJ open
INTRODUCTION: Studies addressing the development and/or validation of diagnostic and prognostic prediction models are abundant in most clinical domains. Systematic reviews have shown that the methodological and reporting quality of prediction model s...

Guidelines for clinical trials using artificial intelligence - SPIRIT-AI and CONSORT-AI.

The Journal of pathology
The rapidly growing use of artificial intelligence in pathology presents a challenge in terms of study reporting and methodology. The existing guidelines for the design (SPIRIT) and reporting (CONSORT) of clinical trials have been extended with the a...

The implications of emerging technology on military human performance research priorities.

Journal of science and medicine in sport
OBJECTIVES: To demonstrate the need for the military human performance research community to anticipate and evolve with the emergence of new and disruptive battlefield technologies that are changing the fundamental role of the human combatant.