Machine-learning algorithms are 13% more accurate in predicting the surgical time needed in the operating room compared with human schedulers, according to new US research.
An algorithm developed using artificial intelligence could soon be used by doctors to diagnose heart attacks with better speed and accuracy than ever before, according to new research.
An artificial intelligence developed at TU Wien (Vienna) can suggest appropriate treatment steps in cases of blood poisoning. The computer has already surpassed humans in this respect.
Autism spectrum disorder (ASD) is a developmental disorder associated with difficulties in interacting with others, repetitive behaviors, restricted interests and other symptoms that can impact academic or professional performance.
A UK research team has developed a new technique that combines machine learning with short-wave infrared (SWIR) fluorescence imaging to detect precise boundaries of tumors.
Predicting a Covid-19 infection from the sound of a cough? Researchers found that technology using Machine Learning performed no better than simply asking people to report their symptoms.
US researchers are developing a highly accurate machine learning model for early detection of mild cognitive impairment and dementia in older drivers.
The risk for poor glycemic control in patients with type 2 diabetes can be predicted with confidence by using machine learning methods, a new study from Finland finds.
A new study demonstrates that AI models, using symptom and demographic features, can help predict Covid-19 infections, providing a way for rapid screening and cost-effective infection detection.
In surgery, artificial intelligence (AI) is applied mostly in imaging, navigation, and robotic intervention. However, AI can also play a major role in preoperative planning. Objective decisions-making, optimal utilisation of operating theatres and less overtime are additional advantages that are achieved with the use of AI in surgery.
Deaths from cancer are currently estimated at 10 million each year worldwide. Conventional cancer staging systems aim to categorize patients into different groups with distinct outcomes. ‘However, even within a specific stage, there is often substantial variation in patient outcomes,’ Markus Plass, academic researcher from the Medical University of Graz, Austria, explained to Healthcare in…
Clinical management of soft tissue sarcoma is particularly challenging. Dr Sebastian Foersch, researcher at the Institute of Pathology at the University Medical Center in Mainz, Germany, has used a deep learning model for diagnosis and prognosis prediction of soft tissue sarcoma using conventional histopathology slides.
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.