Alzheimer’s disease is a neurodegenerative disorder that causes memory loss and problems in cognitive functions. ML genetic healthcare expert Dr Sara Moein showcases ML applications in the diagnosis and prognosis of the disease, along with the development of drugs to treat it.

ML genetic and healthcare data specialist Dr Sara Moein details the intricacies of the ETL process for extracting, transforming, and loading data, and its implications for healthcare, which are of especial significance as the industry’s digitalization continues to gather steam.

Gene expression is the process through which information inscribed into a gene is converted into a function. ML genetic and healthcare data specialist Dr Sara Moein relates how ML accurately predicts target genes from landmark ones and states the implications of this in medicine.

ML use in peptide prediction is a key emerging application, one which sheds light on the body’s immune system and its response to antigens. ML genetic and healthcare data specialist Dr Sara Moein explains how this works.

Single-cell RNA sequencing is a mighty weapon in cancer research that maps cell types and states, both individually and in clusters. ML then pares down the ensuing reams of data for ease of analysis. ML genetic and healthcare data specialist Dr Sara Moein explains their workings.

Intelligent methods help medical professionals detect and diagnose COVID-19 more quickly and so expedite treatment for patients suffering from severe cases, as ear, nose, and throat specialist Dr Mehrnaz Ataei and genetic and healthcare ML developer Dr Sara Moein succinctly explain.

ECG signals are vital in spotting cardiac disorders but are prone to ‘noise’ that hides heart problems from doctors. Genetic and healthcare ML developer Dr Sara Moein explains the intelligent methods that brush this ‘snow’ interference from such indicators to add clarity to ECGs.

Various Big Data sources - EHRs, omics data, medical images, signals, videos - provide reams of precise information in support of healthcare. Genetic and healthcare data machine learning developer Sara Moein presents an overview of the future of healthcare Big Data has opened up.

Cell type morphology in histological images is an indicator that detects diseases like cancer. Pathologists can apply the cell shape to spot abnormalities. Dr Sara Moein explains how automatic detection of cell types helps pathologists work quicker and more efficiently.

Deep learning technologies are revolutionizing the diagnosis and prognosis of complicated diseases and cancer. Intelligent medical diagnosis expert Dr Sara Moein predicts the role of AI in 2023 in medical diagnosis and healthcare.

Medical machine learning researcher Sara Moein explains how AI methods take advantage of physics equations and phenomena from nature, and offers examples of how these methods apply in healthcare.

AI methods are being applied in various areas, including the detection of the best medications for curing diseases. In this article, Dr Sara Moein explains how intelligent methods help doctors administer the best medications to achieve the best outcomes after Systemic-Pulmonary Arterial shunt surgery in newborns.

Machine learning, artificial intelligence and other smart methods are poised to turbocharge the work of pathologists. Follow medical machine learning researchers Sara Moein as she conducts a tour of these technologies and hints at what the future holds in store.

Detecting heart disorders from electrocardiogram (ECG) signals is no easy task as noise often corrupts ECG signals. Dr Sara Moein presents different approaches for AI to serve cardiologists for more accurate, quicker heart disorder diagnoses.

Dr Sara Moein explains how AI predicts the outcomes of heart surgery in children and presents details about using the pediatric health information system database to design an intelligent model to identify patients at higher risk of complications from surgery to avert adverse outcomes.

Dr Sara Moein discusses the role of artificial intelligence in detecting mental health disease and explains various data structures that AI applies to identify the hidden patterns for mental health diagnosis and treatment.