About The Event
This event has now ended. Below are the event proceedings.
FACULTY OF HEALTH SCIENCES
JAMES LIND INSTITUTE,
GENEVA, SWITZERLAND
October 19th, 2024
2:00 PM CET
INTRODUCTION OF THE EVENT
The Faculty of Health Sciences at the James Lind Institute, Switzerland, recently hosted a Virtual Workshop on The Role of Artificial Intelligence in Depression Management. The workshop commenced with an introduction to the James Lind Institute, a Swiss EduQua-certified international educational institution based in Geneva, Switzerland. The institute is dedicated to preparing students for careers in public health, health administration, pharmaceutical sciences, clinical research, economics, diplomacy, business management, and beyond. It boasts a network of over 5000 alumni spanning across 80+ countries globally.
TARGET AUDIENCE OF THE EVENT
1. Public health workers and professionals
2. Healthcare practitioners, researchers
3. Students pursuing public health courses
4. People from other diverse professional backgrounds
DETAILS OF THE EVENT
1. The introduction of the event shed light on the innovative technologies aiding in reshaping the landscape of mental healthcare. One of the most prevalent and common mental disorders and conditions affecting millions worldwide is Depression. According to the World Health Organization (WHO) estimation, 250 million, i.e., 5% people of the world’s adult population are affected by Depression. Unfortunately, facts state that 75% of the people living in low- or middle-income countries do not receive adequate treatment for such mental conditions. Factors such as accessibility, and timely intervention, act as obstacles rather than facilitating the process. This is where artificial intelligence comes into play for understanding, diagnosing, and managing depression and other such mental disorders.
2. Continuing this, the moderator of the event, Dr. Anahita Ali, welcomed the Expert Speaker of the event, Dr. Farrokh Alemi, Professor of Health Informatics, at George Mason University, Washington, United States. The Speaker is an Operations Researcher and Industrial Engineer with having wealth of experience in academia and the health industry. He is a holder of various patents on Sentiment Analysis and Personalized Medicine. His research focuses on the causal analysis of Electronic Health Records contributing to predictive medicine, precision medicine, comparative effectiveness of medications, and predicting prognosis of patients with multiple mobilities, to name a few. His role in online patient management pioneered the publication of several books.
3. With this, Dr. Alemi took over the session by giving a presentation on “AI SYSTEM FOR MANAGEMENT OF PATIENTS WITH MAJOR DEPRESSIVE DISORDER: PROGRESS PLANS”. He emphasized the fact that the current situation of depression is unacceptable. The majority of the patients as against a “minority” receive inappropriate medications for the diagnosed disorders. More than 60% of the patient’s first anti-depression is inappropriate. In addition to this, there are a large number of issues to be addressed as well. Studies indicate a repeated behavior of patients as well as clinicians who only tend to seek medications one after the other to speedily overcome the issue. This shows that not all kinds of anti-depression are or work the same for every individual.
4. According to a study, 16,700 types of patients exist, for whom different types of anti-depressions could be prescribed way beyond their clinical capabilities.
5. Dr. Alemi emphasized his analysis of the situation as aforementioned and its way out. His AI system is built on the data of 3.6 Million Depressed Patients of whom 10.2 Million treatment episodes have occurred over 16,700 patient subgroups.
6. His findings so far show that his Predictive Model is 17.5% more accurate than average conditions, that is to say, if medications are prescribed as per his Predictive Model, 17.5% more patients benefit from it than the current situations. Currently 40% benefit from the first prescription which would be added by 17.5% to result in 57.5% which is not the ultimate goal but is better in the prevailing situation.
7. The next question so addressed by Dr. Alemi was how to collect relevant information, which according to his model is predicted to be 1,499 Medical History Events relevant in deciding which anti-depressant is the best which is way beyond human capabilities to take into account. Factors such as treatment procedures in the past, the kind of diagnosis the patient has had, the age factor, and experiences with the prescribed anti-depressant, all affect the next anti-depressant experience.
8. Dr. Alemi suggested two approaches, one of the approaches is to gradually ask the patient(s) the questions.
9. The second approach would be to visit MeAgainMeds available on http://MeAgainMeds.com which facilitates a questionnaire format.
10. The Model facilitates predicting the best anti-depressant because such predictions are backed by adequate data which was showcased by an example by Dr. Alemi.
11. Through this model, Dr. Alemi and his team look forward and expect to create an autonomous, safe, conversational, more accurate than clinicians, and free AI system for behavioral care.
12. He addressed a loophole wherein traditional clinicians only address the patient’s mental disorder through a set pattern that is not tailor-made. However, the Model so curated helps the patients find tailor-made prescriptions for their mental disorders based on the questions.
13. Question: What are the ethical considerations for using depression management?
Answer: Dr. Alemi re-questioned by stating what are the ethical considerations for prescribing medications to depressed patients THAT DON’T WORK. According to him, it is criminal to prescribe medications to depressed patients that don’t favor them. He also emphasized that he doesn’t find a problem in some ethical issues with AI methods when clinicians are failing to address the issues of their patients. He also emphasized that patients find AI systems more emphatic towards them in addressing their problems than clinicians. However, he also mentioned that AI systems are not yet ready to completely replace human beings but only to aid them.
14. With the question-answer round, Dr. Anahita Ali concluded the Workshop by underscoring the insightful expertise of Dr. Farrukh Alemi.
PICTURES FROM THE EVENT
