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The Use of Artificial Intelligence in Medicine: Present and Future – Part I

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by Meenakshi Bhattacharjee
From the beginning of the history of computers, scientists have dreamed of creating an electronic brain. Of all the modern technological quests, this search to create artificial intelligent (AI) computer systems has been one of the most ambitious and, not surprisingly, controversial. Scientists and doctors alike were captivated by the potential such a technology might have on medicine. With intelligent computers able to store and process vast amounts of knowledge, the hope was that they would become the perfect “Doctors in the box” assisting or surpassing clinicians with tasks like diagnosis.
With this motivation a small but talented community of computer technologists and doctors set about shaping a research program for a new discipline of study called Artificial Intelligence in Medicine (AIM).These researchers had a bold vision of the was that AIM would revolutionize medicine. Much has changed since then and today this definition would be considered narrow in scope and vision. Today the importance of diagnosis as a task requiring computer support in routine clinical situations receives much less emphasis.
Peak into the uses of AI
Artificial intelligence already found several areas in healthcare to revolutionize starting from the design of treatment plans through the assistance in repetitive jobs to medication management or drug creation. And it is only the beginning.
Mining medical records:
The most obvious application of artificial intelligence in healthcare is data management. Collecting it, storing it, normalizing it, tracing its lineage – it is the first step in revolutionizing the existing healthcare systems. Recently, the AI research branch of the search giant, Google, launched its Google Deep mind Health project, which is used to mine the data of medical records in order to provide better and faster health services.
Designing treatment plans:
IBM Watson launched its special program for oncologists which is able to provide clinicians evidence-based treatment options. Watson for Oncology has an advanced ability to analyze the meaning and context of structured and unstructured data in clinical notes and reports that may be critical to selecting a treatment pathway. Then by combining attributes from the patient’s file with clinical expertise, external research and data, the program identifies potential treatment plans for a patient.
Assisting repetitive jobs:
IBM launched another algorithm called Medical Sieve. It is an ambitious long-term exploratory project to build a next generation “cognitive assistant” with analytical, reasoning capabilities and a wide range of clinical knowledge. Medical Sieve is qualified to assist in clinical decision making in radiology and cardiology. The “cognitive health assistant” is able to analyze radiology images to spot and detect problems faster and more reliably. Radiologists in the future should only look at the most complicated cases where human supervision is useful.
Getting the most out of in-person and online consultations:
The British subscription, online medical consultation and health service, Babylon launched an application this year which offers medical AI consultation based on personal medical history and common medical knowledge. Users report the symptoms of their illness to the app, which checks them against a database of diseases using speech recognition. After taking into account the patient’s history and circumstances, Babylon offers an appropriate course of action. The app will also remind patients to take their medication, and follow up to find out how they’re feeling. Through such solutions the efficiency of diagnosing patients can increase by multiple times, while the waiting time in front of doctor’s examining rooms could drop significantly.


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