Prevalence of self-reported food allergy in Tunisia: General trends and probabilistic modeling.

Background: Food allergy (FA) has become a major public health concern affecting millions of children and adults worldwide. In Tunisia, published data on FA are scarce.

Methods: This study, was intended to fill the gap and estimate the frequency of allergy to different foods in the Sfax region, Tunisia, within self-reported FA.

Applying digital technology to promote active and healthy confinement lifestyle during pandemics in the elderly.

Although recognized as effective measures to curb the spread of the COVID19 outbreak, social distancing and home confinement have generated a mental health burden with older adults who are considered to be more vulnerable to psychosocial strains. To date, the application of digital technologies in response to COVID-19 pandemic has been narrowed to public-health needs related to containment and mitigation. However, information and communications technology (ICT)-based initiatives directed toward prediction and prevention of psychosocial support are still limited.

NovidChain: Blockchain-based privacy-preserving platform for COVID-19 test/vaccine certificates.

The COVID-19 pandemic has emerged as a highly transmissible disease which has caused a disastrous impact worldwide by adversely affecting the global economy, health, and human lives. This sudden explosion and uncontrolled worldwide spread of COVID-19 has revealed the limitations of existing healthcare systems regarding handling public health emergencies. As governments seek to effectively re-establish their economies, open workplaces, ensure safe travels and progressively return to normal life, there is an urgent need for technologies that may alleviate the severity of the losses.

Q-Rank: Reinforcement Learning for Recommending Algorithms to Predict Drug Sensitivity to Cancer Therapy.

In personalized medicine, a challenging task is to identify the most effective treatment for a patient. In oncology, several computational models have been developed to predict the response of drugs to therapy. However, the performance of these models depends on multiple factors.