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 tests whether a non-invasive brain stimulation technique called tDCS can improve social communication and reduce repetitive behaviors in adolescents with autism. Researchers will use machine learning to analyze brain activity (EEG) and clinical data to predict who will…

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 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 when a child may need a palliative care consultation. Researchers will compare outcomes before and after the model is used, involving …

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 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 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…

This study aims to develop an AI model that estimates a patient's blood volume from ultrasound videos of major blood vessels. Researchers will record ultrasound clips from 800 adults scheduled for surgery and compare them to a reliable blood volume measurement. The goal is to cre…