ABSTRACT
Technology and medicine follow a parallel path during the last decades. Technological advances are changing the concept of health and health needs are influencing the development of technology. Artificial intelligence (AI) is made up of a series of sufficiently trained logical algorithms from which machines are capable of making decisions for specific cases based on general rules. This technology has applications in the diagnosis and follow-up of patients with an individualized prognostic evaluation of them. Furthermore, if we combine this technology with robotics, we can create intelligent machines that make more efficient diagnostic proposals in their work. Therefore, AI is going to be a technology present in our daily work through machines or computer programs, which in a more or less transparent way for the user, will become a daily reality in health processes. Health professionals have to know this technology, its advantages and disadvantages, because it will be an integral part of our work. In these two articles we intend to give a basic vision of this technology adapted to doctors with a review of its history and evolution, its real applications at the present time and a vision of a future in which AI and Big Data will shape the personalized medicine that will characterize the 21st century.
Subject(s)
Artificial Intelligence , Robotics , Algorithms , Big Data , Humans , Precision MedicineABSTRACT
BACKGROUND: The wide scale and severity of consequences of tobacco use, benefits derived from cessation, low rates of intervention by healthcare professionals, and new opportunities stemming from novel communications technologies are the main factors motivating this project. Thus, the purpose of this study is to assess the effectiveness of an intervention that helps people cease smoking and increase their nicotine abstinence rates in the long term via a chat-bot, compared to usual practice, utilizing a chemical validation at 6 months. METHODS: Design: Randomized, controlled, multicentric, pragmatic clinical trial, with a 6-month follow-up. SETTING: Healthcare centers in the public healthcare system of the Community of Madrid (Madrid Regional Health Service). PARTICIPANTS: Smokers > 18 years of age who attend a healthcare center and accept help to quit smoking in the following month. N = 460 smokers (230 per arm) who will be recruited prior to randomization. Intervention group: use of a chat-bot with evidence-based contents to help quit smoking. CONTROL GROUP: Usual treatment (according to the protocol for tobacco cessation by the Madrid Regional Health Service Main variable: Continuous nicotine withdrawal with chemical validation (carbon monoxide in exhaled air). Intention-to-treat analysis. Difference between groups in continuous abstinence rates at 6 months with their corresponding 95% confidence interval. A logistic regression model will be built to adjust for confounding factors. RESULTS: First expected results in January 2020. DISCUSSION: Providing science-based evidence on the effectiveness of clinical interventions via information technologies, without the physical presence of a professional, is essential. In addition to being more efficient, the characteristics of these interventions can improve effectiveness, accessibility, and adherence to treatment. From an ethics perspective, this new type of intervention must be backed by scientific evidence to circumvent pressures from the market or particular interests, improve patient safety, and follow the standards of correct practices for clinical interventions. TRIAL REGISTRATION: ClinicalTrials.gov, reference number NCT03445507.
