AIMC Topic: Diagnosis, Computer-Assisted

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Weakly-supervised learning for lung carcinoma classification using deep learning.

Scientific reports
Lung cancer is one of the major causes of cancer-related deaths in many countries around the world, and its histopathological diagnosis is crucial for deciding on optimum treatment strategies. Recently, Artificial Intelligence (AI) deep learning mode...

Defining heterogeneity of epicardial functional stenosis with low coronary flow reserve by unsupervised machine learning.

Heart and vessels
Low CFR is associated with poor prognosis, whereas it is a heterogeneous condition according to the actual coronary flow, such as high resting or low hyperemic coronary flow, which should have different physiological traits and clinical implications....

Machine Learning in Cardiology-Ensuring Clinical Impact Lives Up to the Hype.

Journal of cardiovascular pharmacology and therapeutics
Despite substantial advances in the study, treatment, and prevention of cardiovascular disease, numerous challenges relating to optimally screening, diagnosing, and managing patients remain. Simultaneous improvements in computing power, data storage,...

Major Depressive Disorder Classification Based on Different Convolutional Neural Network Models: Deep Learning Approach.

Clinical EEG and neuroscience
The human brain is characterized by complex structural, functional connections that integrate unique cognitive characteristics. There is a fundamental hurdle for the evaluation of both structural and functional connections of the brain and the effect...

Regulatory considerations for artificial intelligence technologies in GI endoscopy.

Gastrointestinal endoscopy
Artificial intelligence (AI) technologies in clinical medicine have become the subject of intensive investigative efforts and popular attention. In domains ranging from pathology to radiology, AI has demonstrated the potential to improve clinical per...

Deep learning-based reconstruction of ultrasound images from raw channel data.

International journal of computer assisted radiology and surgery
PURPOSE: We investigate the feasibility of reconstructing ultrasound images directly from raw channel data using a deep learning network. Starting from the raw data, we present the network the full measurement information, allowing for a more generic...

Computer-aided diagnosis for fetal brain ultrasound images using deep convolutional neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: Fetal brain abnormalities are some of the most common congenital malformations that may associated with syndromic and chromosomal malformations, and could lead to neurodevelopmental delay and mental retardation. Early prenatal detection of b...