Multinational investment holding conglomerate Tencent is working with the Shanghai Cancer Center to establish an AI-based, big data laboratory to streamline the cancer treatment process, according to a report by Shine, a digital news organization under Shanghai Daily.

Researchers have developed a machine learning system that predicts the severity of arthritis in a pediatric population, allowing for treatment to be personalized. Findings of their research were published in PLOS Medicine.

As the number of diabetes cases continues to rise in India, Google and Verily, the life sciences research organization under Alphabet, have a solution to better screen for the disease and associated eye diseases.

The U.K. Department of Health and Social Care recently issued a new code of conduct for AI systems in an effort to ensure that only the topmost and safest AI-based systems are used by the National Health Service (NHS). 

After seeing success from its AI-powered healthcare bot, Ohio-based healthcare technology company Olive is planning to add 100 tech jobs within the next two years, according to a report by Columbus Business First.

Though the use of AI is still in early stages, its wide-reaching potential is expected to be felt by all industries in the near future. The technology is expected to contribute up to $15.7 trillion to the global economy by 2030, according to a PwC global AI study.

Researchers at the University of Alberta have developed a new AI-based software––Ensemble Algorithm with Multiple Parcellations for Schizophrenia Prediction, or EMPaSchiz––that will allow physicians to identify schizophrenia in fMRI scans with 87 percent accuracy. Their research was published in NJP Schizophrenia.

Dana Solutions, a California-based AI company, is partnering with the FDA’s Center for Drug Evaluation and Research to improve the drug development process by using AI, the company announced Feb. 25.

AI continues to make strides in medicine, with an expected market size in excess of $13 billion by 2025. But physicians and medical school deans at the Imagine Solutions Conference in Naples, Florida, stressed there is no substitute for the patient-physician relationship. 

A new machine learning model allows for physicians to determine whether atypical ductal hyperplasia (ADH) could upgrade to cancer, according to new research published in JCO Clinical Cancer Informatics. The model can identify 98 percent of all malignant cases prior to surgery, while sparing 16 percent of women from unnecessary surgeries.