By using machine learning algorithms, researchers examined if creating a large-scale electronic health record (EHR) data-based lung cancer cohort could be effective in studying a patient’s...
A recent JAMA study highlights risk factors associated with the severity of COVID-19 in individuals using machine learning models and predictive analytics. By studying COVID-19 severity and risk...
Scientists at the University of Illinois Chicago have introduced a new system that uses a machine learning algorithm and predictive analytics to find what transcription factors are most likely to be...
Weill Cornell Medicine announced its $1.5 billion “We’re Changing Medicine” campaign, which intends to advance biomedical innovations in areas such as precision medicine, artificial...
Researchers developed a statistical predictive analytics model that studies patterns in drug-related fatality data and can identify which counties are at high risk for future fatal overdoses, according...
Realyze Intelligence, a company launched recently by The University of Pittsburgh Schools of the Health Sciences (UPMC), will use natural language processing and artificial intelligence to pinpoint...
Researchers developed a machine learning model that uses predictive analytics to detect a COVID-19 patient’s risk of death or dialysis treatment, a new study published in the Clinical Journal of...
Applying machine learning to wearable device data could help predict clinical laboratory measurements without a visit to the doctor’s office, a new study published in Nature Medicine reveals. The...
Researchers effectively trained machine learning models to predict the risk of gastrointestinal bleeding (GIB) within six to twelve months of a patient being prescribed antithrombotic drugs, according...
Using a dataset of electronic health records along with survey results, machine learning algorithms utilized artificial intelligence to communicate patient satisfaction improvement recommendations,...
Across the healthcare industry, leaders are increasingly leveraging real-time data analytics tools to advance insights and improve decision-making.
In high-risk care settings, these tools are...
Researchers at the University of California San Diego have developed an artificial intelligence algorithm that can help robots better navigate the ED.
The team has also developed a dataset of...
Machine learning can measure unconsciousness in patients under anesthesia, allowing anesthesiologists to optimize drug doses, according to a study published in PLOS One.
Anesthetic drugs act on the...
Using machine learning, clinicians may be able to choose which imaging test to use for patients who may have coronary artery disease, a condition caused by plaque buildup in the arterial wall.
Yale...
Machine learning can quickly analyze EHR data to identify chronic kidney disease, a condition which often goes undetected until it causes irreversible damage, a study published in npj Digital Medicine...
A mobile app was able to distinguish toddlers diagnosed with autism spectrum disorder using machine learning, indicating that the technology could someday serve as a scalable early screening tool.
In...
A machine learning algorithm could help public health officials identify COVID-19-related conspiracy theories on social media, potentially reducing the spread of misinformation online, a study...
For organizations that want to deepen their knowledge of disease risk and health outcomes, genomic data has emerged as a comprehensive resource that can provide clinicians with new insights.
While the...
Genomic data can provide more targeted insights into chronic disease management than those generated from traditional ethnic or racial labels like Hispanic or Black, a study published in Cell...
Researchers at MIT’s Data to AI Lab (DAI Lab) have developed a new framework that can streamline machine learning processes to help organizations uncover actionable insights from big data.
The...
