AIMC Topic: Humans

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Alzheimer's diagnosis using deep learning in segmenting and classifying 3D brain MR images.

The International journal of neuroscience
BACKGROUND AND OBJECTIVES: Dementia is one of the brain diseases with serious symptoms such as memory loss, and thinking problems. According to the World Alzheimer Report 2016, in the world, there are 47 million people having dementia and it can be 1...

Evaluation of machine learning-driven automated Kleihauer-Betke counting: A method comparison study.

International journal of laboratory hematology
INTRODUCTION: The Kleihauer-Betke (KB) test is the diagnostic standard for the quantification of fetomaternal hemorrhage (FMH). Manual analysis of KB slides suffers from inter-observer and inter-laboratory variability and low efficiency. Flow cytomet...

Topology-guided cyclic brain connectivity generation using geometric deep learning.

Journal of neuroscience methods
BACKGROUND: There is a growing need for analyzing medical data such as brain connectomes. However, the unavailability of large-scale training samples increases risks of model over-fitting. Recently, deep learning (DL) architectures quickly gained mom...

The opportunities and challenges of machine learning in the acute care setting for precision prevention of posttraumatic stress sequelae.

Experimental neurology
Personalized medicine is among the most exciting innovations in recent clinical research, offering the opportunity for tailored screening and management at the individual level. Biomarker-enriched clinical trials have shown increased efficiency and i...

Radiomic Detection of EGFR Mutations in NSCLC.

Cancer research
Radiomics is defined as the use of automated or semi-automated post-processing and analysis of multiple features derived from imaging exams. Extracted features might generate models able to predict the molecular profile of solid tumors. The aim of th...

Artificial intelligence CT screening model for thyroid-associated ophthalmopathy and tests under clinical conditions.

International journal of computer assisted radiology and surgery
PURPOSE: Thyroid-associated ophthalmopathy (TAO) might lead to blindness and orbital deformity. The early diagnosis and treatment are conducive to control disease progression, but currently, there is no effective screening method. The present study a...

Automatic sleep scoring: A deep learning architecture for multi-modality time series.

Journal of neuroscience methods
BACKGROUND: Sleep scoring is an essential but time-consuming process, and therefore automatic sleep scoring is crucial and urgent to help address the growing unmet needs for sleep research. This paper aims to develop a versatile deep-learning archite...

Patch-based classification of gallbladder wall vascularity from laparoscopic images using deep learning.

International journal of computer assisted radiology and surgery
PURPOSE: In this study, we propose a deep learning approach for assessment of gallbladder (GB) wall vascularity from images of laparoscopic cholecystectomy (LC). Difficulty in the visualization of GB wall vessels may be the result of fatty infiltrati...