Artificial intelligence can help doctors early diagnose diseases
Clincial diagnosis can be more accurate and rapid if artificial intelligence is used to assist the clinician.
By combining deep learning and machine learning with the medical world, Enlitic, a company that has followed in the footsteps of IBM's Watson and Microsoft's InnerEye in launching initiatives for the use of artificial intelligence in medicine and health, hopes to aid doctors in the development of more effective treatment methods and the early diagnosis of diseases. aims.
With the use of Enlitic artificial intelligence technology, which was developed with the objective of enabling doctors to perform more effective and accurate evaluations through deep learning, it may be possible to detect the ailment using images obtained using the radiography approach (the medical method in which rays of different wavelengths and sound waves are used in the diagnosis and treatment of diseases).
By 2020, it is projected that the total global quantity of patient data will exceed 25,000 petabytes (1 petabyte equals 1024 terabytes). When a large amount of data is combined with deep learning technology, it is possible to make considerable progress in disease diagnosis.
Certain solutions may be provided by the artificial intelligence application that has been developed. These are the ones to look out for:
1. Patient triage
Every year in the United States, over 300 million radiological examinations are requested for diagnostic purposes. With a growing number of patients, radiologists will find it increasingly difficult to score these exams accurately and precisely. The newly created artificial intelligence program can scan the clinical findings of arriving patients in order to determine their priorities and direct them to the most appropriate clinician. This allows a medical image to be read in milliseconds, which is 10,000 times faster than a radiologist's reading time.
Second,
cancer screening programs are used to diagnose cancer at an early stage. Cancer screening tests are becoming increasingly popular in today's society. The artificial intelligence tool that has been built recognizes potentially concerning instances that arise as a result of screening tests and notifies the radiologist, allowing physicians to work more effectively despite the high volume of patients. Among other things, Enlitic is 50 percent more accurate than qualified radiologists in identifying potentially malignant lesions in a computed tomography image obtained for a lung cancer patient who has undergone chemotherapy.
3. On-the-spot clinical assistance:
According to the National Institute of Health, 12 million cases of misdiagnosis occur in the United States each year. Because of the effective technologies that will be developed for accurate disease diagnosis, this number can be drastically lowered in a short period of time. In addition to providing therapeutic support, the artificial intelligence program that has been developed can assist clinicians in evaluating difficult cases. To give an example, deep learning technology can detect even the tiny fractures that cover only a thousandth of an X-ray image with high accuracy.
Rather than attempting to develop a technology that will replace radiologists, the developers of Enlitic claim that they are attempting to develop artificial intelligence technology that will allow radiologists to do their jobs much more quickly. They also claim to be working on issues such as the development of new drugs and laboratory tests.
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