Documents Médecine - Informatique 3 résultats

- 1 ressource en ligne (x, 147 pages) : illustrations

Médecine - Informatique

Big data plays an increasingly important role in today's practice of otolaryngology and in all of healthcare. In Big Data in Otolaryngology, Dr. Jennifer Villwock leads a team of expert authors who provide a comprehensive view of many key impacts of big data in otolaryngology--including understanding what big data is and what we can and cannot learn from it; best practices regarding analysis; translating findings to clinical care and associated cautions; ethical issues; and future directions. Covers the clinical relevance of big data in otolaryngology, lessons and limitations of large administrative datasets, biologic big data, and much more. Discusses artificial intelligence (AI) in otolaryngology and its clinical application. Presents a patient perspective on big data in otolaryngology and its use in clinical care, as well as a glimpse into the future of big data. Compiles the knowledge and expertise of leading experts in the field who have assembled the most up-to-date recommendations for managing big data in otolaryngology. Consolidates today's available information on this timely topic into a single, convenient resource.

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- 203 p.
Cote : W 26.55.A7 B581d 2023

Médecine - Informatique ; Intelligence artificielle

Nous sommes en passe d'inventer les machines qui nous soigneront mieux que nous sommes capables de nous soigner nous-mêmes. L'intelligence artificielle se dressera bientôt contre la maladie, avec une implacable efficacité." Médecin-chercheur en cancérologie à Paris, après avoir travaillé à Stanford dans la Silicon Valley, Jean-Emmanuel Bibault est aussi un geek de la première heure. Adolescent dans les années 1990, il programme des jeux et crée un site-hommage à son réalisateur préféré, Stanley Kubrick. Devenu chef de clinique, sa thèse sur le Machine Learning appliquée à la cancérologie est distinguée par l'Académie nationale de médecine. Dans ce premier livre à destination du grand public, il montre comment les techniques d'intelligence artificielle bouleversent la pratique de la médecine. De l'épidémiologie au traitement, en passant par chaque étape du parcours de soins, et dans toutes les spécialités. Alors que la médecine s'apprête à vivre des changements radicaux, Jean-Emmanuel Bibault questionne les enjeux de cette révolution et nous plonge dans la peau du patient du futur. Une odyssée captivante à l'horizon 2040.

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- xiii, 378 p. : ill.
Cote : W 26.55.A7 T674d 2019

Intelligence artificielle ; Médecine - Informatique ; Diagnostics - Informatique

A visit to a doctor these days is often cold, mechanical-robotic. Eye contact is scarce. Physicians spend much of their time typing. The brief, depersonalized visits lead to misdiagnoses and medical errors. Despite having access to more resources than ever, our doctors are overloaded with demands for their time and expertise.
In Deep Medicine, leading physician Eric Tobol shows how artificial intelligence can help. Natural-language processing can record our doctors' notes, make sense of our medical histories, and read more deeply into the scientific literature than any human ever could. Deep-learning algorithms – applied to wearable sensors, genomic information, blood work, scans, and all of our medical data – can create bespoke treatment plans. And virtual medical assistants, powered by personalized AI, can provide us with coaching to promote our health, shape our diet, and even prevent illness. But most importantly, by freeing physicians from the tasks that interfere with human connection, AI will give doctors the gift of time – to restore the care in healthcare.
Innovative, provocative, and hopeful, Deep medicine shows us how the awesome power of AI can make medicine better, and reveals the paradox that machines can make humans healthier – and more human.

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