AI News, Artificial intelligence and the future of medicine artificial intelligence

My vision for the future of AI healthcare – Enthusiast perspective

Healthcare enthusiast According to a report by Accenture, the market value of artificial intelligence in the medical field is forecasted to reach $6.6 billion by 2021.

Artificial intelligence mostly refers to automating tasks that can be completed by machines, thus, reducing workload and freeing up time for humans.

This unlocks time for medical professionals to spend with their patients allowing for the provision of more efficient, patient-centric care.

Automation not only has the potential to improve patient outcomes but allows healthcare providers such as the National Health Services in the UK to realise huge productivity gains and cost reductions.

As technology changes the face of medicine, the patient narrative and the user journey need to be considered very carefully.

As Bertalan Meskó, The Medical Futurist aptly captured AI will be “the stethoscope of the 21st century”, playing a critical role in medicine.

Dr. AI Will See You Now: Machines and the Future of Medicine

Experts have estimated that AI applications can potentially create $150 billion in annual savings for the U.S. healthcare economy by 2026, and AI can address an estimated 20 percent of unmet clinical demand.

In the wrong hands, it’s clear that AI tools could be misused, but with the right strategies and careful use of AI aligned with an organization’s goals, AI can be used to generate insights based on data and analytics that may have been otherwise missed.

AI has the potential to improve the quality of care and reduce cost by preventing unnecessary tests and procedures, while accelerating diagnoses and improving access by better utilizing resources.

In the current healthcare climate, adding value while improving patient outcomes and access is not only a stated goal but also an imperative for survival of health systems in the emerging value-based integrated care environment.

For timely results, health systems may need to invest in a data hub that can be used to stage data for AI models, as well as GPU-based compute environment that allows researchers to train and optimize AI systems.

From visualization, which presents information to clinicians clearly and succinctly, to integration of AI information with workflows, all the way to automated decisions, which act on ever-evolving algorithms, analytics and AI are key to a practical and effective architecture.

large concern from healthcare leaders around establishing an AI architecture is cost—all that data can come at a hefty price for organizations of all sizes, not to mention the costs associated with hiring the proper experts and training team members.

And, despite the associated costs, AI is no longer just a flashy option for healthcare organizations—it can also provide a distinct advantage in both quality of care and business performance, as AI leaders have begun to see evidence of in their organizations.

Gluck has over 20 years of experiencedirecting information technology initiatives, managing complex IT projects, leading technical and professional teams, and providing critical business strategy support.

5 Ways Artificial Intelligence May Affect Health Care in the Near Future and What That Means for You

Concepts that were mere science fiction only a couple of decades ago --like artificial intelligence (AI) --are quickly becoming commonplace.

machine learning algorithms are more accurate and faster than ever;and the cloud and the internet of things have made it possible for even small devices to access artificial intellgence'senormous capabilities.

Instead of blindly following a checklist, AI digital consultation systems have learned from millions of real case files to ask questions that are relevant to the particular patient.

With computer vision technology, systems can be trained to look at x-rays or other scans and apply deep learning to understand what images show.

In November, for example, the University of Rochester Medical Center announced that it was using tech from Aidoc, an AI radiology company, to help identify and prioritize critical cases so that urgent-care patients could be seen by a radiologist first, giving those patients the best of both worlds: AI and a doctor together.

Personalized medicine today is kind of a utopian buzz term: a health care approach where diagnoses and treatments are highly tailored to meet the patient’s personal and family history as well as his or her specific risk factors and genetics.

There have been robot solutions for surgery for years, including the advanced da Vinci system, that allows surgeons to take control of precision robotic equipment to perform minimally invasive procedures.

The Smart Tissue Autonomous Robot (STAR) can already suture stitches that are cleaner and more accurate than what a human surgeon can do;and early tests show the technology can also accurately remove a tumor with less damage to the surrounding tissue.

Earlier this year, health care cybersecurity vendor CyberMDX discovered a vulnerability in a popular syringe pump that could allow an attacker to take over the device and administer lethal dosages of medication.

Advanced cybersecurity solutions could use machine learning to understand normal network behavior and identify and block any anomalous activities that could indicate vulnerabilities or attacks.

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