“One is as diagnostic aid clinical decision support tools, and AI tool can help triage the patients that need the most amount of care,” said Dr. Po-Hao Chen, Chief Informatics Officer for the Cleveland Clinic Imagining Institute.
Dr. Chen showed Fox 8 some examples of how AI is helping shorten the time it takes to perform an MRI to detecting, diagnosing, and quickly treating both breast cancer and stroke patients.
“Before the patient even hits the interventional suite just coming out of the scanner, we can get the doctors ready we can get the nurses and everyone and start talking about a case,” he said.
Currently there are literally hundreds of AI programs and algorithms being created and considered across the country he says as the field is exploding in several ways.
“That is the challenge that we as physicians, as stewards of our patients have to do due diligence on what qualifies as deployable,” he said, “So just because it’s cleared by the FDA that doesn’t always mean that it’s ready to be deployed in our hospital for our patients.”
Recently the Cleveland Clinic opened the first Quantum Computer in healthcare, and they say it’s being used to develop potential treatments for Alzheimer’s, cancer immunotherapies, guiding complex brain surgeries and again helping with early detection of cancers including breast cancer.
“So, we’re pretty excited about all of the work that’s going on,” said Dr. Chen.
Here are some more examples of treatments that are part of Discovery Accelerator in partnership with IBM shared with Fox 8 News.
Identifying existing drugs with potential to treat Alzheimer’s disease—There is an urgent need for effective Alzheimer’s disease treatments. This collaboration is developing intelligent computer-based systems and other analytic tools to search databases of human gene sequences and the molecular targets of existing drugs, looking for matches that could indicate therapeutic potential in Alzheimer’s disease and dementia. The most promising AI-predicted re-purposable drugs could then be tested using large-scale data. Technologies developed here could be applied to other complex diseases.
Developing next-generation cancer immunotherapies—Immunotherapy can improve the power of the immune system to detect and destroy cancer cells, slowing or preventing tumor growth. This project will use AI and physics-based models to identify and optimize epitopes, which are the targets that immune cells recognize. Epitopes are the basis for development of new cancer immunotherapies and vaccines.
Assessing anti-inflammatory drugs’ effect on epilepsy seizures—Patients with epilepsy who undergo cranial surgery may experience postoperative seizures. This project will use AI to explore an extremely large dataset containing insurance claim information to determine if the administration of certain drugs to reduce inflammation also reduced the occurrence of seizures after brain surgery. Positive correlation will then be assessed by studying a smaller patient population where detailed clinical information is available.
AI Guiding Complex Brain Surgery
Artificial intelligence and machine learning are revolutionizing the way large volumes of patient data are interpreted – leading to more precise epilepsy surgical planning.
Advanced Imaging for Epilepsy
Cleveland Clinic’s epilepsy team is using advanced imaging, such as, and AI to help locate the source of seizures. Epileptic seizures are caused by abnormal electrical activity in the brain, so neurologists need to locate the source of that abnormal activity. Cleveland Clinic’s epilepsy team is using advanced imaging, such as MRI fingerprinting and AI to help locate brain lesions causing seizures. Epileptic seizures are caused by abnormal electrical activity in the brain. Brain lesions may be the cause of seizures and removing these lesions can give patients a cure for epilepsy.
AI to Speed up Stroke Diagnosis
AI software that can automatically detect large vessel occlusion, alert the doctor whose job it is to remove the blockage, and trigger a process that we developed where the neurologist, radiologist and surgeon immediately assemble in a virtual “chat room” to review the patient’s case together and decide on the best course of action. The technology complements the trained eye of the radiologist, creating synergy between the human and AI. Precious minutes are saved, and with them brain function.
AI in Breast Cancer Screening
AI-based computer-aided detection (CAD) in breast digital tomosynthesis, commonly known as 3D mammography, which has improved the accuracy and efficiency of these exams. By leveraging advanced algorithms and machine learning techniques, AI not only helps radiologists detect subtle cancers with greater precision, but also contributes to reduction of false positives.
AI in the ICU
Cleveland Clinic is currently beginning to use preliminary models to predict the trajectory of ICU patients. The ICU is a data rich environment, as patients are closely monitored. Instead of checking on patients once or twice a day, AI uses minute to minute data to flag if a patient is, for example at risk for delirium or further decline that would require additional intervention. This information could help physicians intervene soon and avoid complications.