MACHINE LEARNING

This study is developing a computer program that can listen to a newborn's heartbeat using a digital stethoscope and tell if it sounds normal or not. The goal is to catch serious heart problems early, reduce false alarms, and lower healthcare costs. Researchers will record heart …

This study tests whether a computer can predict which teenagers with autism will respond well to a gentle brain stimulation technique called tDCS. Researchers will measure brain activity with EEG and collect behavioral data before treatment, then see if these can tell apart those…

This study tests whether a new system that uses routine health records and data from a smartphone app can predict asthma attacks in children and young people aged 5 to 17. Researchers will monitor 900 participants, focusing on those at high risk, to see if the system reduces the …

This study tests whether a machine learning model can predict which children will need a targeted medication in the next three months. The goal is to help doctors order pharmacogenetic testing beforehand, so they can choose the right drug or dose. About 275 children aged 6 months…

This study aims to develop a new way to estimate a patient's blood volume before surgery using ultrasound videos and artificial intelligence. Currently, there is no easy, non-invasive method to measure blood volume accurately. Researchers will record ultrasound videos of major bl…

This study looks at whether measuring blood flow in the stomach and intestines can help predict which critically ill patients will have trouble with tube feeding. Researchers will monitor 500 ICU patients and use machine learning to build prediction models. The goal is to improve…

This study is testing whether a machine-learning model can help doctors identify children admitted to the hospital for heart problems who might benefit from a palliative care consultation. The model will flag high-risk patients each morning, and doctors will decide whether to ref…

This study tests whether machine learning can accurately predict when spinal anesthesia ends after total knee replacement. Researchers will use patient data like age and surgery details to train computer models. The goal is to help doctors plan better care and improve patient rec…