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The Practical Guide to the Future of Medicine

I wrote a book “The Guide to the Future of Medicine: Technology AND The Human Touch” to prepare everyone for the coming waves of change, to be a guide for the future of medicine that anyone can use. It describes 22 trends and technologies that I think will shape the future.

Read about the real examples and practical stories related to why these are leading the waves of change in my Linkedin post.

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Augmented Reality Mirror in Telemedicine

A great article was published about how augmented reality mirrors will take telepresence to a new level.

They have invented a system that utilizes a camera and a flat panel display that will provide you an experience of looking at the mirror. The system utilizes technologies like augmented reality and adaptive image transformation for implementing this. When the image stream from the camera is displayed on the screen, it appears to mimic a reflection in a mirror, rather than a recorded video stream.

The opportunities it could provide in medicine are imminent:

A doctor can use this mirror for patient diagnostic and patient monitoring. For example, better imaging could be used for diagnosing skin problems, cancer, melanoma, breast changes that can suggest further testing for breast cancer, eye problems, spine, bones, muscles and body flexibility trends and changes.

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Philips to Enroll Hereismydata™ Worldwide

My mentor and good friend, Lucien Engelen, Director of the Radboud REshape Innovation Center did it again! He transformed a great idea that can save a lot of lives globally into an actual product or service. Today, he announced that Philips will start enrolling Hereismydata worldwide in front of 140.000 people at the 3rd biggest IT event of the world, “Dreamforce” of Salesforce.com.

We at Hereismydata™ are creating a one-stop-and-go place to store your data. Secure, robust and you in control. Connecting apps and devices, creating clinical modules like the COPD module with Philips, and connecting services like Apple’s healthkit and (lateron) Google Fit and back and forth EMR’s will help to create insight in the patchwork of data out there.

They start with COPD but will add many more conditions soon. Combining all kinds of vendors, operating systems, and languages as well as local legislation issues that have been tackled creates the ecosystem he envisioned long ago.

This video explains how it works.

IBM Watson Takes Next Step

Last week, I wrote about how stakeholders of medicine could and should prepare for IBM Watson’s use in medical decision making to get the most out of it. I highlighted the importance of investing in natural language processing.

And what do they announce this week? First a global expansion and then that they create a natural language question answering system.

Cognition is in virtually everything that humans do, such as language understanding, perception, judgment, motor skills, learning, spatial processing and social behavior. Increasingly, we expect the machines that we use to exhibit the same cognitive behavior. IBM Watson represents a first step into cognitive systems, a new era of computing. In addition to using programmatic computing, Watson has three capabilities that make it truly unique: Natural language processing, Hypothesis generation, and evaluation Dynamic learning

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Interview about the future on MobileHealthGlobal.com

Teresa Bau, Editor of Mobile Health Global, interviewed me about my new book, The Guide to the Future of Medicine, my views regarding how healthcare will change in the coming years with mobile health and in what technologies I see the most potentials. An excerpt from the interview:

Doctor Bertalan Meskó (@berci) has published The Guide to the Future of Medicine, a book highly anticipated by professionals from the health and new technologies sectors. The book anticipates and gives and overview on how health and healthcare will work in the near future. Meskó, doctor in genomics and author of Webicina-a well-known website which provides health resources- was one of the speakers at the Barcelona’s MI Health Forum.

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Medical Futurist to Forecast the New Era of Healthcare at ASCP Annual Meeting in Tampa

This is the title of the press release the American Society for Clinical Pathology published today about my keynote that I will give in this year’s meeting in Tampa. I look forward to talking about the future of genomics, wearable technologies and the patient-physician partnership, among others.

An excerpt from the press release:

“We are thrilled to announce that Dr. Meskó is hosting a general session at this year’s annual meeting,” commented Dr. E. Blair Holladay, CEO/Executive Vice President of ASCP. “His session will be an invigorating discussion on ways that new technology, such as genomics and next-generation sequencing, are providing pathologists and medical laboratory professionals with valuable tools to improve patient care.”

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Why And How Healthcare Institutions Should Prepare For IBM Watson

What even the most acclaimed professors know cannot match cognitive computers. As the amount of information they accumulate grows exponentially, the assistance of computing solutions in medical decisions is imminent. While a physician can keep a few dozen study results and papers in mind, IBM’s supercomputer named Watson can process million pages in seconds. This remarkable speed has led to trying Watson in oncology centers to see how helpful it is in making treatment decisions in cancer care.

Watson is based on deep Q&A technology and gives a set of possible answers as the most relevant and likely outcomes to medical questions. But physicians make the final call. I have to note here that Watson is not there to replace the physicians, but to support them when making decisions. It also interacts with physicians and can suggest which additional tests are needed to generate a higher degree of confidence.

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The MD Anderson Center’s Oncology Expert Advisor

It is built to aid physicians in making evidence-informed decisions based on up-to-date knowledge. The system was designed to have three main capabilities:

  • Dynamic patient summary: Interpret structured and unstructured clinical data to create dynamic patient case summaries.
  • Evidence-based treatment options: Make treatment and management suggestions based on the patient profile weighed against consensus guidelines, relevant literature, and MD Anderson expertise.
  • Care pathway advisory: Provide care pathway advice that supports management of patients by alerting clinicians of adverse events or suggesting proactive care support.

When testing the accuracy of the system to recommend standard of care treatment related to 200 leukemia cases, the system had a false-positive rate of 2.9% and a false-negative rate of 0.4%. The overall accuracy of the standard of care recommendations was 82.6%.

The Memorial Sloan Kettering Oncology Advisor

Memorial Sloan Kettering’s expertise and experience with thousands of patients are the basis for teaching Watson how to translate data into actionable clinical practice based on a patient’s unique cancer. While initially focused only on breast and lung cancers, the work has expanded to more than a dozen other common solid and blood cancers such as colon, prostate, bladder, ovarian, cervical, pancreas, kidney, liver, and uterine, as well as melanomas and lymphomas. Watson digested the guidelines about Lung and Breast Cancer issued by the National Comprehensive Cancer Network (roughly 500,000 unique combinations of breast cancer patient attributes; and roughly 50,000 unique combinations of lung cancer patient attributes). Over 600,000 pieces of evidence were digested from 42 different publications/publishers.

How to prepare

There is no doubt it will have a bigger and bigger impact on how we practice medicine worldwide. But all stakeholders in the system must prepare for that:

  1. Medical professionals should acquire basic knowledge about how AI works in a medical setting in order to understand how such solutions might help them in their everyday job.
  2. Decision makers at healthcare institutions should do everything to be able to measure the success and the effectiveness of the system. This is the only way to assess the quality of AI’s help in medical decision making.
  3. Companies such as IBM should communicate even more towards the general public about the potential advantages and risks of using AI in medicine.
  4. Non-English speaking countries should invest in natural language processing (NLP). If the patient information is not in English, Watson needs to understand the content and context of the structured and unstructured information in that language. To do this, it uses the Unified Medical Language System (UMLS) and a semantic type recognition. The Watson Content Analytics (WCA) tool that processes NLP and is based on Unstructured Information Management Architecture (UIMA) is used for building annotations. WCA then uses a Medical Concept Extraction Tool and a Health Language Medical Terminology Management system that uses standard medical terminologies databases such as SNOMED, ICD-9, ICD-10, RxNorm, etc. And this is where most e.g. European countries miss the point. They don’t have all these systems in all the languages.

The other option is obviously to train physicians and nurses to document everything in English. But we can agree that this will never happen.

It is time to prepare in order to let technology help us do a better job in medicine.

This video provides a great summary about all these:

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