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AccessMedicine home page Home. Access Provided by: Googlebot. Books Behavioral Medicine: A Guide for Clinical Practice, 4e. Mitchell D. Feldman, John . Escolha sua região: Presidente Prudente / SP · Brasília/DF · Curitiba / PR · Florianópolis/SC · Goiania / GO · Sao Paulo / SP. Online shopping for Books from a great selection of Medicine, Psychology, Basic Sciences, Administration & Medicine Economics, Nursing, Pharmacology.
As Topol admits, there are few controlled trials in this field. Most of the research is at the stage of algorithm validation by technology companies, and we still lack examples of AI improving outcomes in the real world of clinical practice. We are in the first act of what will probably be a five-act play.
The problem is evident: health care has become a massively expensive enterprise that no longer serves the needs of doctors and patients. In wealthy countries, the costs continue to grow without commensurate improvements in outcomes. In poorer regions, the lack of health-care workers becomes unsustainable as the population and its needs expand. And the setting for this play is appealing: a sea of data from online behaviour, sensors, smartphones, genome scans, imaging, lab tests and clinical records.
If data are the new oil, health data — which Topol describes as between six and ten times as valuable as financial data — are the refined petroleum that AI can inject into diagnostic and treatment decisions. But big data is not the same as good data.
For most health-care questions, we might not have the information to find a solution. For instance, we recognize the role of social determinants in health but rarely collect data on them. And even if the data were optimal, the algorithms accurate and the diagnostic process improved, would doctors choose to be present? Would they be educated to be empathetic and compassionate? Deep Medicine wrestles with these questions, recognizing that technology is about tools, whereas medicine is about a person-to-person bond.
The first, The Creative Destruction of Medicine , focused on sensors and sequencing as a pathway for digitizing medicine. The second, The Patient Will See You Now , described how practice could be transformed by empowering people with their own health data. Like these, Deep Medicine is about technology and health care, but it evolves surprisingly towards the values of the past while imagining the tools of the future. When Topol describes how medicine has changed since his training four decades ago, one feels his regret that technology has not improved things.
He addresses that by bringing together the deep phenotyping of digitized medicine, the engagement of the empowered patient and the analytical power of AI to improve the doctor—patient relationship. He invites us to dream about what the AI future could look like, while reminding us that we need to be drivers, not just passengers, if AI is to serve patients and clinicians rather than payers and tech monopolies.
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