AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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Issues associated with deploying CNN transfer learning to detect COVID-19 from chest X-rays.

Physical and engineering sciences in medicine
Covid-19 first occurred in Wuhan, China in December 2019. Subsequently, the virus spread throughout the world and as of June 2020 the total number of confirmed cases are above 4.7 million with over 315,000 deaths. Machine learning algorithms built on...

Predicting antibody affinity changes upon mutations by combining multiple predictors.

Scientific reports
Antibodies are proteins working in our immune system with high affinity and specificity for target antigens, making them excellent tools for both biotherapeutic and bioengineering applications. The prediction of antibody affinity changes upon mutatio...

The emergence of new trends in clinical laboratory diagnosis.

Saudi medical journal
Diagnostic processes typically rely on traditional and laborious methods, that are prone to human error, resulting in frequent misdiagnosis of diseases. Computational approaches are being increasingly used for more precise diagnosis of the clinical p...

Privileged Scaffold Analysis of Natural Products with Deep Learning-based Indication Prediction Model.

Molecular informatics
Natural products play a vital role in the drug discovery and development process as an important source of reliable and novel lead structures. But the existing criteria for drug leads were usually developed for synthetic compounds and cannot be direc...

Non - invasive modelling methodology for the diagnosis of coronary artery disease using fuzzy cognitive maps.

Computer methods in biomechanics and biomedical engineering
Cardiovascular diseases (CVD) and strokes produce immense health and economic burdens globally. Coronary Artery Disease (CAD) is the most common type of cardiovascular disease. Coronary Angiography, which is an invasive approach for detection and tre...

Machine learning-based prediction of acute coronary syndrome using only the pre-hospital 12-lead electrocardiogram.

Nature communications
Prompt identification of acute coronary syndrome is a challenge in clinical practice. The 12-lead electrocardiogram (ECG) is readily available during initial patient evaluation, but current rule-based interpretation approaches lack sufficient accurac...

Accurate deep-learning estimation of chlorophyll-a concentration from the spectral particulate beam-attenuation coefficient.

Optics express
Different techniques exist for determining chlorophyll-a concentration as a proxy of phytoplankton abundance. In this study, a novel method based on the spectral particulate beam-attenuation coefficient (c) was developed to estimate chlorophyll-a con...

A comprehensive study on the multi-class cervical cancer diagnostic prediction on pap smear images using a fusion-based decision from ensemble deep convolutional neural network.

Tissue & cell
The diagnosis of cervical dysplasia, carcinoma in situ and confirmed carcinoma cases is more easily perceived by commercially available and current research-based decision support systems when the scenario of pathologists to patient ratio is small. T...

In Silico Prediction of Metabolic Epoxidation for Drug-like Molecules via Machine Learning Methods.

Molecular informatics
Epoxidation is one of the reactions in drug metabolism. Since epoxide metabolites would bind with proteins or DNA covalently, drugs should avoid epoxidation metabolism in the body. Due to the instability of epoxide, it is difficult to determine epoxi...