ChatGPT in Occupational Medicine: A Comparative Study with Human Experts.

The objective of this study is to evaluate ChatGPT's accuracy and reliability in answering complex medical questions related to occupational health and explore the implications and limitations of AI in occupational health medicine. The study also provides recommendations for future research in this area and informs decision-makers about AI's impact on healthcare. A group of physicians was enlisted to create a dataset of questions and answers on Italian occupational medicine legislation. The physicians were divided into two teams, and each team member was assigned a different subject area. ChatGPT was used to generate answers for each question, with/without legislative context. The two teams then evaluated human and AI-generated answers blind, with each group reviewing the other group's work. Occupational physicians outperformed ChatGPT in generating accurate questions on a 5-point Likert score, while the answers provided by ChatGPT with access to legislative texts were comparable to those of professional doctors. Still, we found that users tend to prefer answers generated by humans, indicating that while ChatGPT is useful, users still value the opinions of occupational medicine professionals.

Embedded Systems and TensorFlow Frameworks as Assistive Technology Solutions.

In the field of deep learning, this paper presents the design of a wearable computer vision system for visually impaired users. The Assistive Technology solution exploits a powerful single board computer and smart glasses with a camera in order to allow its user to explore the objects within his surrounding environment, while it employs Google TensorFlow machine learning framework in order to real time classify the acquired stills. Therefore the proposed aid can increase the awareness of the explored environment and it interacts with its user by means of audio messages.

Bioimpedance based monitoring system for people with neurogenic dysfunction of the urinary bladder.

Patients with impaired bladder volume sensation have the necessity to monitor bladder level in order to avoid urinary tract infections and urinary reflux that can lead to renal failure. In this paper the the effectiveness of an embedded and wearable solution for bladder volume monitoring using the bioimpedance measurement is tested. Data are streamed real-time using Bluetooth wireless technology. The bioimpedance measurements on a healthy subject prove the effectiveness of the proposed solution. In the future the system will be evaluated in real world scenarios with patients affected by spinal paralysis and bladder neurogenic dysfunction.