MACHINE LEARNING

This study is developing a computer program that can analyze heart sounds recorded with a digital stethoscope to tell if a newborn's heart is healthy or not. Researchers will record heart sounds from 1,000 babies under 30 days old and use those recordings to train and test the pr…

This study will enroll 900 children aged 5-17 with asthma to see if remote monitoring—using routine health data and a smartphone app—can predict asthma attacks. Researchers will track whether this system reduces the number of attacks compared to past averages. A subset of high-ri…

This study is developing a machine learning model to predict the risk of relapse within one year for people with allergic bronchopulmonary aspergillosis (ABPA), a lung condition caused by an allergic reaction to a fungus. Researchers will collect data from 300 patients across mul…

This study looks at whether measuring blood flow in the stomach and intestines can help predict feeding intolerance in critically ill patients. Researchers will monitor 500 ICU patients receiving tube feeding and track symptoms like vomiting, bloating, or diarrhea. The goal is to…

This study tests whether a machine learning model can predict which children admitted to the hospital will need a medication that requires genetic testing. The goal is to offer the test earlier, so doctors can pick the safest drug or dose. The trial will involve 275 children aged…

This study aims to find out if brain activity measured by EEG and other clinical data can predict which teenagers with autism will improve after a non-invasive brain stimulation treatment called tDCS. Researchers will treat 90 adolescents with autism and track changes in social a…

This study aims to create a computer model that can predict how soon patients will walk on their own after hip or knee replacement surgery. Researchers will collect data from about 943 patients who had surgery and physical therapy. The goal is to help doctors plan better care, bu…

This study tests whether a machine-learning model can predict serious heart events in children admitted to the hospital. The model alerts doctors each morning about high-risk patients, so they can decide if a palliative care team should be involved. Researchers will compare what …

This study aims to develop a new, non-invasive way to estimate a patient's blood volume before surgery using ultrasound videos and artificial intelligence. Researchers will record ultrasound clips of major blood vessels from 800 adult patients and use a deep learning model to pre…

This study looks at whether machine learning (a type of artificial intelligence) can accurately predict how long spinal anesthesia lasts in people having knee replacement surgery. Researchers will use patient information like age, surgery details, and anesthesia data to train com…