It’s widely known that more than 70% of today’s medical decisions involve the results of laboratory tests, but the insights clinicians derive from these tests today may only be scratching the surface of their potential.
US scientists and engineers have found a way to improve the performance of traditional Magnetic Resonance Imaging (MRI) reconstruction techniques, allowing for faster MRIs to improve healthcare.
An international team of researchers advises that strong care needs to be taken not to misuse or overuse machine learning (ML) in healthcare research, despite all of its benefits.
A new system capable of reading lips with remarkable accuracy even when speakers are wearing face masks could help create a new generation of hearing aids.
Machine learning and artificial intelligence (AI) have the potential to transform cancer treatment management worldwide. Their ability to rapidly analyse and integrate routinely acquired diverse data will improve the accuracy and effectiveness of precision medical treatments.
Researchers for the first time compared schizophrenia and frontotemporal dementia, disorders that are both located in the frontal and temporal lobe regions of the brain.
Researchers developed an AI that accurately and quickly diagnoses idiopathic pulmonary fibrosis, based only on information from lung images and medical information collected during daily medical care.
Patients are 20% less likely to die of sepsis because a new AI system developed at Johns Hopkins University catches symptoms hours earlier than traditional methods, an extensive hospital study shows.
MIT researchers produced textiles that sense the wearer’s posture and motions. Their “smart” shoes and mats could be used in applications ranging from health care to prosthetics.
The classification of brain tumors—and thus the choice of optimal treatment options—can become more accurate and precise through the use of artificial intelligence in combination with physiological imaging.
An artificial intelligence (AI) model combining four methods of machine learning (ML) to accurately detect thyroid cancer from routine ultrasound image data has been developed by US researchers.
Computational approaches are being applied on enormous amounts of data from sequencing technologies to develop tools to help clinicians manage cancer more effectively.
Artificial intelligence (AI) could help guide the post-treatment surveillance of non-small cell lung cancer (NSCLC) patients and improve outcomes as a result, according to a new study.
The motion capture technology called Precise Marker-less could aid doctors and physiotherapists in their consultations and diagnoses for patients in need of rehabilitation.
Scientists have utilized the integration of lightweight material engineering and artificial intelligence to create an exoskeleton robot that can aid those with mobility impairments.
Researchers have developed a noninvasive and reagent-free technique for the efficient detection of COVID-19.
Researchers from Israel have developed a technology that rectifies the effects of underrepresentation of women in clinical trials using machine learning models.
Researchers used artificial intelligence to identify sets of genes that predict whether a patient will acquire severe sepsis.
A new pilot study suggests that machine learning algorithms which fuse electrocardiogram (ECG) and electronic health record data may help doctors screen for dangerous, lung-clogging blot clots.
Researchers in the UK and China have developed an AI model that can diagnose Covid-19 as well as a panel of professional radiologists, while preserving the privacy of patient data.
A novel artificial intelligence score provides a more accurate forecast of the likelihood of patients with suspected or known coronary artery disease dying within 10 years than established scores used by health professionals worldwide. The research was presented at EuroEcho 2021, a scientific congress of the European Society of Cardiology (ESC).
Researchers at the McKelvey School of Engineering at Washington University in St. Louis found a way to significantly reduce the noise and maintain image quality while reducing the laser energy needed to generate images by 80%.
Researchers have leveraged the power of digital pathology and computational modeling to detect and quantify podocytes, a specialized type of cell in the kidney that undergoes damaging changes during early-stage kidney disease.
Researchers at King's College Hospital and Queen Mary University of London have shown that a new computer-based algorithm can rank drugs used to treat primary liver cancer, based on their efficacy in reducing cancer cell growth.
Machine learning methods are being used to predict the health of the placenta from a 30-second MRI scan. Researchers hope the approach will offer an insight into the health of expectant mothers and unborn babies by detecting the early signs of dangerous conditions such as pre-eclampsia. Researchers from the School of Biomedical Engineering & Imaging Sciences at King’s College London (KCL)…
