AI Medical Compendium Topic

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PhthisisBioMed Artificial Medical Intelligence: Software for Automated Analysis of Digital Chest X-ray/Fluorograms.

Sovremennye tekhnologii v meditsine
The scope of diagnostic medical examinations increases from year to year causing a reasonable desire to develop and implement new technologies to diagnostics and medical data analysis. Artificial intelligence (AI) algorithms became one of the most pr...

Development of Debiasing Technique for Lung Nodule Chest X-ray Datasets to Generalize Deep Learning Models.

Sensors (Basel, Switzerland)
Screening programs for early lung cancer diagnosis are uncommon, primarily due to the challenge of reaching at-risk patients located in rural areas far from medical facilities. To overcome this obstacle, a comprehensive approach is needed that combin...

Machine and Deep Learning for Tuberculosis Detection on Chest X-Rays: Systematic Literature Review.

Journal of medical Internet research
BACKGROUND: Tuberculosis (TB) was the leading infectious cause of mortality globally prior to COVID-19 and chest radiography has an important role in the detection, and subsequent diagnosis, of patients with this disease. The conventional experts rea...

A deep learning approach to estimate x-ray scatter in digital breast tomosynthesis: From phantom models to clinical applications.

Medical physics
BACKGROUND: Digital breast tomosynthesis (DBT) has gained popularity as breast imaging modality due to its pseudo-3D reconstruction and improved accuracy compared to digital mammography. However, DBT faces challenges in image quality and quantitative...

COVID-19 Severity Prediction from Chest X-ray Images Using an Anatomy-Aware Deep Learning Model.

Journal of digital imaging
The COVID-19 pandemic has been adversely affecting the patient management systems in hospitals around the world. Radiological imaging, especially chest x-ray and lung Computed Tomography (CT) scans, plays a vital role in the severity analysis of hosp...

Initial study on an expert system for spine diseases screening using inertial measurement unit.

Scientific reports
In recent times, widely understood spine diseases have advanced to one of the most urgetn problems where quick diagnosis and treatment are needed. To diagnose its specifics (e.g. to decide whether this is a scoliosis or sagittal imbalance) and assess...

COV-MobNets: a mobile networks ensemble model for diagnosis of COVID-19 based on chest X-ray images.

BMC medical imaging
BACKGROUND: The medical profession is facing an excessive workload, which has led to the development of various Computer-Aided Diagnosis (CAD) systems as well as Mobile-Aid Diagnosis (MAD) systems. These technologies enhance the speed and accuracy of...

Patient Identification Based on Deep Metric Learning for Preventing Human Errors in Follow-up X-Ray Examinations.

Journal of digital imaging
Biological fingerprints extracted from clinical images can be used for patient identity verification to determine misfiled clinical images in picture archiving and communication systems. However, such methods have not been incorporated into clinical ...

Explainable COVID-19 Detection Based on Chest X-rays Using an End-to-End RegNet Architecture.

Viruses
COVID-19,which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the worst pandemics in recent history. The identification of patients suspected to be infected with COVID-19 is becoming crucial to reduce its spr...

3D surface reconstruction of cellular cryo-soft X-ray microscopy tomograms using semisupervised deep learning.

Proceedings of the National Academy of Sciences of the United States of America
Cryo-soft X-ray tomography (cryo-SXT) is a powerful method to investigate the ultrastructure of cells, offering resolution in the tens of nanometer range and strong contrast for membranous structures without requiring labeling or chemical fixation. T...