By using artificial intelligence, Houston Methodist researchers are able to predict hospitalization outcomes of geriatric patients with dementia on the first or second day of hospital admission. This early assessment of outcomes means more timely interventions, better care coordination, more judicious resource allocation, focused care management and timely treatment for these more vulnerable, high-risk patients. Because geriatric patients with dementia have longer hospital stays and incur higher health care costs than other patients, the team sought to solve this problem by identifying modifiable risk factors and developing an artificial intelligence model that improves patient outcomes, enhances their quality of life and reduces their hospital readmission risk, as well as reducing hospitalization costs once the model is put into practice. The study, appearing online Sept. 29 in Alzheimer's & Dementia: Translational Research and Clinical Interventions, looked at the hospital records of 8,407 geriatric patients with dementia over 10 years within Houston Methodist's system of eight hospitals, identifying risk factors for poor outcomes among subgroups of patients with different types of dementia that stem from diseases such as Alzheimer's, Parkinson's, vascular dementia and Huntington's, among others. From this data, the researchers developed a machine learning model to quickly recognize the predictive risk factors and their ranked importance for undesirable hospitalization outcomes early in the course of these patients' hospital stays.

Columbia University professor and robotics engineer Hod Lipson knows the importance of artificial intelligence (AI) on a global level. "It permeates everything we do, from the stock market, from predicting the weather to what product you're going to buy," he said Wednesday during the second day of the virtual Ai4 2020 conference. AI falls into the category of an exponential technology, meaning it accelerates with time. Both biopharma and med-tech companies are increasingly pulling the technology into their business operations, working on programs that can assist in everything from drug discovery and clinical trial recruitment to precision diagnostics and patient compliance efforts. Computing power has doubled every 20 months or so for the past 120 years, Lipson said, moving from mechanical instruments to graphics processing units (GPUs) today.

New research will be live in npj Digital Medicine on December 12, 2019, that will feature a machine learning app aimed at preventing patients from severe fall-related injuries and death. This AI technology was developed by Houston Methodist and tested over an eight-month period to help address the growing concern of severe patient falls with seniors and the worry it causes their care-providers and care-givers. The AI app predicts the risk of getting injured when a patient falls. Clinical parameters and patient demographics such as bone density, diagnosis, past procedures, etc. are used to populate the app so it then triggers tailored interventions to prevent these high-risk severe injury patients from falling - whether they are in the hospital setting or with home caregivers. This AI technology can be integrated into the patient's electronic medical record (EMR) and make things easier for clinicians since it will be part of the record and will automatically flag or alert the care-providers for high risk fall with harm patients when they enroll in the hospital.

Matthew Schubert, emergency services manager for Houston Methodist The Woodlands Hospital, talks about how the LUCAS chest compression system works beside Chief Medical Officer Jason Knight, Friday, July 26, 2019. Matthew Schubert, emergency services manager for Houston Methodist The Woodlands Hospital, talks about how the LUCAS chest compression system works beside Chief Medical Officer Jason Knight, Friday, July 26, 2019. A quick reaction time is critical when an individual has a heart attack, but the quality of CPR performed to get someone's heart working again is also essential. Houston Methodist The Woodlands Hospital now has a new robotic device that can perform CPR more consistently than any human team. "This is a game changing device," Matthew Schubert said as he explained how the LUCAS 3 device works. Schubert is the manager of emergency services at the hospital.

Researchers at Houston Methodist have developed an artificial intelligence (AI) software that reliably interprets mammograms, assisting doctors with a quick and accurate prediction of breast cancer risk. According to a new study published online Aug. 29 in Cancer, the computer software intuitively translates patient charts into diagnostic information at 30 times human speed and with 99 percent accuracy. "This software intelligently reviews millions of records in a short amount of time, enabling us to determine breast cancer risk more efficiently using a patient's mammogram. This has the potential to decrease unnecessary biopsies," said Stephen T. Wong, Ph.D., P.E., chair of the Department of Systems Medicine and Bioengineering at Houston Methodist Research Institute. The team led by Wong and Jenny C. Chang, M.D., director of the Houston Methodist Cancer Center used the AI software to evaluate mammograms and pathology reports of 500 breast cancer patients.