Sooraj Shah ’24 The detection of fractures via radiography is one of the most highly used practices in clinical settings such as the emergency room, urgent care, orthopedic and rheumatology offices. The missed fracture diagnosis rate is between 1-3%, accounting for almost 1,200 of every 100,000 patients. A major cause of missed fractures is erroneous initial readings by residents or non-radiologists, which are only corrected … Continue reading AI-Assisted Readings May Greatly Improve Fracture Diagnosis
Figure 1: Young female holding the hand of a humanoid robot. Julia Chivu ’24 Children may be more open to robots than humans when it comes to their mental health. The growing rate of anxiety and depression among children in the United Kingdom motivated researchers to utilize this unique technology as they sought out better mental health resources in the wake of the COVID-19 pandemic. … Continue reading The Role of Robots in Mental Health Detection For Children
Lydia Wang ’26 Human faces and the ability to recognize different facial identities have played a key role in evolution. It has been observed that human faces have evolved to uniquely distinguish themselves from others. However, many people know someone they resemble; some comparisons are so similar that they are labeled as a doppelgänger, or a living double. Doppelgängers have been an ongoing phenomenon that … Continue reading Are Doppelgängers Really Just a Coincidence?
Ishmam Khan ’25 Deep learning involves the use of machinery to simulate biological phenomena, especially human behavior. Researchers have developed two systems of programming that proved useful in mimicking movements: convolutional neural networks (CNNs), which are based on virtual imagery and spatial information, and recurrent neural networks (RNNs), which adapt long-short term memory (LSTM) to model long term contextual information of temporal sequences. When used … Continue reading Optimizing Movement-Based Behavior Networks in Artificial Intelligence