For Bengaluru resident Srishti Shekhar, the stay-at-home situation and her last year of school made her try something she had never done before: online consultation to solve her acne issues. "I had been to two dermatologists before coming across Remedico's service on Instagram. The sign-up process was very easy and all I had to do was send a few photos and I had a treatment plan designed for me within a day," says Shekhar. Like Shekhar, thousands of Indians turned to the internet when going to a clinic seemed risky. By September, the number of internet subscribers in India had risen to 776.45 million, up from 718.74 million in December 2019--474.11

Clinical decision support systems combine knowledge and data from a variety of sources, represented by quantitative models based on stochastic methods, or qualitative based rather on expert heuristics and deductive reasoning. At the same time, case-based reasoning (CBR) memorizes and returns the experience of solving similar problems. The cooperation of heterogeneous clinical knowledge bases (knowledge objects, semantic distances, evaluation functions, logical rules, databases...) is based on medical ontologies. A multi-agent decision support system (MADSS) enables the integration and cooperation of agents specialized in different fields of knowledge (semiology, pharmacology, clinical cases, etc.). Each specialist agent operates a knowledge base defining the conduct to be maintained in conformity with the state of the art associated with an ontological basis that expresses the semantic relationships between the terms of the domain in question. Our approach is based on the specialization of agents adapted to the knowledge models used during the clinical steps and ontologies. This modular approach is suitable for the realization of MADSS in many areas.

Task 2 is a task on semantic similarity between clinical cases and discussions. For this task, we propose an approach based on language models and evaluate the impact on the results of different preprocessings and matching techniques. For task 3, we have developed an information extraction system yielding very encouraging results accuracy-wise. We have experimented two different approaches, one based on the exclusive use of neural networks, the other based on a linguistic analysis.

Beauty is getting a high-tech face lift. Clinique has been a legacy cosmetics and skincare brand for 50 years. But now it's appealing to fresh-faced millennials and Gen Z shoppers with an app that uses selfies to help select the perfect products for a customer's unique complexion. The free Clinique Clinical Reality app launching Jan. 1 invites users to snap a close-up of their face, and then answer a few questions about their skin, such as how many products they use in their daily routine. Then they get matched with customized recommendations.