Learning and fine-tuning a generic value-selection heuristic inside a constraint programming solver.

Constraint programming is known for being an efficient approach to solving combinatorial problems. Important design choices in a solver are the , designed to lead the search to the best solutions in a minimum amount of time. However, developing these heuristics is a time-consuming process that requires problem-specific expertise.

Patients' testimonies, feelings, complaints and emotional experiences with dermatoses on open social media: The French infodemiologic patient's free speech study.

Background: Dermatoses represent a significant burden. Patients and their caregivers can turn to social media and digital communities to exchange with each other. These public exchanges constitute real-life data that can be analysed to better understand the patients' feelings and expectations, and the daily difficulties encountered.

HLA antibody affinity determination: From HLA-specific monoclonal antibodies to donor HLA specific antibodies (DSA) in patient serum.

Organs transplanted across donor-specific HLA antibodies (DSA) are associated with a variety of clinical outcomes, including a high risk of acute kidney graft rejection. Unfortunately, the currently available assays to determine DSA characteristics are insufficient to clearly discriminate between potentially harmless and harmful DSA. To further explore the hazard potential of DSA, their concentration and binding strength to their natural target, using soluble HLA, may be informative.

Identifying Profiles and Symptoms of Patients With Long COVID in France: Data Mining Infodemiology Study Based on Social Media.

Background: Long COVID-a condition with persistent symptoms post COVID-19 infection-is the first illness arising from social media. In France, the French hashtag #ApresJ20 described symptoms persisting longer than 20 days after contracting COVID-19. Faced with a lack of recognition from medical and official entities, patients formed communities on social media and described their symptoms as long-lasting, fluctuating, and multisystemic.

A New Method to Extract Health-Related Quality of Life Data From Social Media Testimonies: Algorithm Development and Validation.

Background: Monitoring social media has been shown to be a useful means to capture patients' opinions and feelings about medical issues, ranging from diseases to treatments. Health-related quality of life (HRQoL) is a useful indicator of overall patients' health, which can be captured online.

Objective: This study aimed to describe a social media listening algorithm able to detect the impact of diseases or treatments on specific dimensions of HRQoL based on posts written by patients in social media and forums.