AIMC Topic: Diagnosis, Computer-Assisted

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Comparing different deep learning architectures for classification of chest radiographs.

Scientific reports
Chest radiographs are among the most frequently acquired images in radiology and are often the subject of computer vision research. However, most of the models used to classify chest radiographs are derived from openly available deep neural networks,...

Generating diagnostic report for medical image by high-middle-level visual information incorporation on double deep learning models.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Writing diagnostic reports for medical images is a heavy and tedious work. The automatic generation of medical image diagnostic reports can assist doctors to reduce their workload and improve diagnosis efficiency. It is of ...

Personal identification with orthopantomography using simple convolutional neural networks: a preliminary study.

Scientific reports
Forensic dental examination has played an important role in personal identification (PI). However, PI has essentially been based on traditional visual comparisons of ante- and postmortem dental records and radiographs, and there is no globally accept...

Improving the accuracy of medical diagnosis with causal machine learning.

Nature communications
Machine learning promises to revolutionize clinical decision making and diagnosis. In medical diagnosis a doctor aims to explain a patient's symptoms by determining the diseases causing them. However, existing machine learning approaches to diagnosis...

Reliability and accuracy of EEG interpretation for estimating age in preterm infants.

Annals of clinical and translational neurology
OBJECTIVES: To determine the accuracy of, and agreement among, EEG and aEEG readers' estimation of maturity and a novel computational measure of functional brain age (FBA) in preterm infants.

Artificial intelligence assistance significantly improves Gleason grading of prostate biopsies by pathologists.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
The Gleason score is the most important prognostic marker for prostate cancer patients, but it suffers from significant observer variability. Artificial intelligence (AI) systems based on deep learning can achieve pathologist-level performance at Gle...

Multicenter Multireader Evaluation of an Artificial Intelligence-Based Attention Mapping System for the Detection of Prostate Cancer With Multiparametric MRI.

AJR. American journal of roentgenology
The purpose of this study was to evaluate in a multicenter dataset the performance of an artificial intelligence (AI) detection system with attention mapping compared with multiparametric MRI (mpMRI) interpretation in the detection of prostate cance...

Development and validation of an explainable artificial intelligence-based decision-supporting tool for prostate biopsy.

BJU international
OBJECTIVES: To develop and validate a risk calculator for prostate cancer (PCa) and clinically significant PCa (csPCa) using explainable artificial intelligence (XAI).

An Automatic Epilepsy Detection Method Based on Improved Inductive Transfer Learning.

Computational and mathematical methods in medicine
Epilepsy is a chronic disease caused by sudden abnormal discharge of brain neurons, causing transient brain dysfunction. The seizures of epilepsy have the characteristics of being sudden and repetitive, which has seriously endangered patients' health...