Creating Emotional AI: Chatbot with Physician-Like Empathy

Overview

Used for diagnosis, preventative screening, treatment, and more, it is undeniable that Artificial Intelligence (AI) is necessary to the future of healthcare technology. Yet drastically, AI falls short of the empathy and compassion humans have. While this may seem unconcerning in a screening sense, as AI continues to be used as a tool of self-diagnosis through chatbots, it is paramount for it to possess the correct skills displayed in physician -patient interactions. This research paper utilizes generative AI and python to create a more empathetic healthcare chatbot. Using both structured prompts and developer instructions, the chatbot is customized to mimic the compassion of human healthcare professionals. The AI is tested on the CARE Measure, a real test used to measure the empathy of healthcare providers. 50 data samples have been collected, and the researcher has found that the AI scored an average of 45.38/50 on the CARE Measure, in comparison to general practitioner scores of 46.53. When conducting Welch' s T -Test, the researcher found a P -value of 2.624(10)-7, which was significantly lower than the significance level, 0.05. With this, the researcher concluded that the null hypothesis was unsupported by the statistics, therefore the hypothesis was supported: AI chatbots incorporating advanced NLP score similarly or higher than human physicians in assessments of empathy areas where healthcare providers are few, or poverty prevents individuals from receiving proper healthcare, AI chatbots provide an accessible and cost-effective solution by delivering medical advice to those who need it. Investigating the Impact of Geometric Properties on Airfoil Performance: A Study of Coefficient of Lift (Cl), Coefficient of Drag (Cd), Coefficient of Moment (Cm), and Stall Angle Nicholas Vail Sigonella Middle High School, FPO, AE Airfoils are used in nearly every field of engineering, from aerospace to environmental applications, and their purpose is not always to generate lift. This study examines the effect of airfoil geometry on aerodynamic performance, specifically lift, drag, moment, and stall characteristics—key indicators of airfoil behavior. The study focuses on maximum camber and thickness, two of the four defining geometric characteristics. It was determined that camber or asymmetry generally increased lift and drag, while decreasing the moment force. In contrast, thickness had the opposite effect. However, both thickness and camber did not seem to have a significant impact on the angle at which the airfoil stalled. A better understanding of airfoils allows for the creation of more efficient machines that save energy, money, and time. This study specifically advanced the understanding of camber and thickness effects on airfoils in common use. It also examined stalls, a characteristic often overlooked due to its subjectivity and difficulty in determination. The study approached this in a nuanced way, incorporating only airfoils in use today and simulating them in a manner that better reflects real flight conditions.

Competition history

• JSHS 2025 Category not listed

Resources

• National JSHS abstract book ↗

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