Qu’est-ce qu’un Data Scientist ? EN
What is a Data Scientist? ALIA SANTé DATA SCIENTIST This professional collects, analyzes and valorizes data. It’s a new job that has emerged throughout the 21st century. But what is the real role of a Data Scientist? Reading time: 3 minutes How does he work? The Data Scientist must transform raw data into usable information using machine learning algorithms.They need to be on many fronts. Curious, they need to be alert to new techniques. He must be able to devise plans of attack. Gather relevant data. But above all, it’s a job that demands great intellectual agility. His or her ability to cross-reference data and elaborate ideas will enable him or her to respond to individual problems. What does it code? This professional generally works on behalf of companies. They are mostly asked to work on a B2B basis. In order for the professional to establish the ideal algorithm, a company will present him/her with its current problem. Through this, the Data Scientist will need to gather the data collected by the company. Thanks to this data, the Data Scientist will develop a state-of-the-art solution, adapted to the company’s needs, in 4 main stages : Data cleansing and storage Data processing Analysis and production of predictions Communication of results Data Scientists in a nutshell Today, there are several routes into this profession. The most conventional route is through university. There are a number of courses up to baccalaureate +6 that allow access to this field of expertise. Mathematics, computer science, statistics… However, these courses are more suited to certain profiles than others. The Data Scientist and his place in the world Working in data science therefore requires a great deal of curiosity. It also requires an unfailing sense of rigor and organization. To be in data science is to be in the future. Indeed, this is one of the professions of the future.
Témoignage Synaxys EN
Testimonial Synaxys ALIA SANTé Read the testimonial from Synaxys, a pioneer in neuro-engineering, who called on Torus Medical to help them realize their project. Reading time: 2 minutes. Parkinson’s disease, Alzheimer’s disease, multiple sclerosis, epilepsy or autism are all terms that are likely to ring a bell. All correspond to disorders or diseases of the nervous system, i.e. diseases that affect, disrupt and sometimes progressively destroy the human nervous system. Treating diseases of the nervous system: a challenge. Today, diseases of the nervous system affect 7% of the world’s population, yet 76% of drug candidates fail to reach Phase III clinical trials. Despite the urgent need to make effective drugs available to patients, no curative treatment yet exists. Clearly, we are facing a major social problem. At the root of this medical wandering is the lack of effective models. All the more so since animal experimentation, which has been widely used up until now, is becoming increasingly controversial and is tending to disappear. The time has come, therefore, to develop new in vitro experimental models to contribute to the development and study of the pathophysiological effects of existing or new drug entities, targeted at diseases of the human nervous system. Optimizing current in vitro models is therefore a key health challenge that Synaxys has been addressing for over 2 years. The Synaxys solution Thanks to innovative patented processes, Synaxys offers “5D-brain“, the first reliable in vitro human model of the nervous system, enabling complex functional studies to be carried out over time. This model, designed for clinical research, is capable of predicting human nervous system responses to treatment. This is the first model to provide three-dimensional, time-correlated functional information (5D). Carrying out multi-parametric analyses leads to problems in processing and analyzing the data collected, due to the multiplicity of formats involved. Source : SYNAXYS | Neuro-Engineering Systems
témoignage certipair EN
CertiPair testimonial ALIA SANTé Discover the testimony of CertiPair, a collaborative base for short medical advice, which called on the expertise of Torus Medical to help it carry out its project. Reading time: 2 minutes. You have just left your medical appointment and yet you have already forgotten your doctor’s advice and/or prescriptions! Don’t worry, you’re not the only one. 95% of medical recommendations are not memorized. Consultations that are too “short” In France in 2017, 2 million consultations are carried out every day by general practitioners. In other words, that amounts to almost 22 17-minute consultations per day. (study conducted by Doctolib from May 1, 2016 to April 26, 2017). It is undeniable that since the COVID-19 health crisis, we can certainly believe that these figures have significantly increased. Among daily consultations, a majority is dedicated to medical monitoring, renewal of treatments as well as diagnosis. In order to care for as many patients as possible, general practitioners try to respect time slots per consultation. This is why these questions follow one another and some patients consider them too short, not having the time to fully understand, remember and ask their questions to the healthcare professional. On the doctor’s side, the lack of time for his patient can influence the relevance of the proposed treatment/monitoring. A solution : CertiPair CertiPair is a SAAS collaborative database that allows healthcare professionals to semi-automatically send recommendations, alerts or advice to their patients by SMS after the ‘too short’ consultation. For example, the user can receive analysis reminders, advice on medical treatments or pre-surgical protocols. Why SMS? The WHO says that SMS affects 85% of the world population compared to 35% for Chatbots and mobile applications. So that the professional can access in just a few clicks the most relevant message (in the secure collaborative database) for a given problem, CertiPair needed to integrate an artificial intelligence algorithmic solution. The goal being to optimize the message search system, through the symbiosis between different information (recognition of text fields, identification of keywords in identified contexts, relevance score based on the expertise of health professionals and frequency of use in particular). We needed to integrate an artificial intelligence algorithmic solution whose aim is to optimize the message search system, through the symbiosis between different pieces of information. Source: CertiPair – Collaborative medical base
