In medicine, at best it becomes a database scraping tool that a doctor plugs diagnostic patient data into for a broader look at potential conditions that the Doctor then takes the output from and goes from there. Think of it like a research assistant that gets high and hallucinates a lot. Subscription service at best with a few market participants, maybe with models tweaked to be more accurate within more definited data sets/specialties.
Porn, well, as always the sky is the limit for porn.
Artificial intelligence (AI) is a powerful and disruptive area of computer science, with the potential to fundamentally transform the practice of medicine and the delivery of healthcare. In this review article, we outline recent breakthroughs in the ...
pmc.ncbi.nlm.nih.gov
AI today (and in the near future)
Currently, AI systems are not reasoning engines ie cannot reason the same way as human physicians, who can draw upon ‘common sense’ or ‘clinical intuition and experience’.
12 Instead, AI resembles a signal translator, translating patterns from datasets. AI systems today are beginning to be adopted by healthcare organisations to automate time consuming, high volume repetitive tasks. Moreover, there is considerable progress in demonstrating the use of AI in precision diagnostics (eg diabetic retinopathy and radiotherapy planning).
AI in the medium term (the next 5–10 years)
In the medium term, we propose that there will be significant progress in the development of powerful algorithms that are efficient (eg require less data to train), able to use unlabelled data, and can combine disparate structured and unstructured data including imaging, electronic health data, multi-omic, behavioural and pharmacological data. In addition, healthcare organisations and medical practices will evolve from being
adopters of AI platforms, to becoming
co-innovators with technology partners in the development of novel AI systems for precision therapeutics.
AI in the long term (>10 years)
In the long term, AI systems will become more
intelligent, enabling AI healthcare systems achieve a state of precision medicine through AI-augmented healthcare and connected care. Healthcare will shift from the traditional one-size-fits-all form of medicine to a preventative, personalised, data-driven disease management model that achieves improved patient outcomes (improved patient and clinical experiences of care) in a more cost-effective delivery system.
Connected/augmented care
AI could significantly reduce inefficiency in healthcare, improve patient flow and experience, and enhance caregiver experience and patient safety through the care pathway; for example, AI could be applied to the remote monitoring of patients (eg intelligent telehealth through wearables/sensors) to identify and provide timely care of patients at risk of deterioration.
In the long term, we expect that healthcare clinics, hospitals, social care services, patients and caregivers to be all connected to a single, interoperable digital infrastructure using passive sensors in combination with ambient intelligence.
31 Following are two AI applications in connected care.