Machine learning not only cuts costs drastically, but also provides diagnostic results in real time. By using four machine learning algorithms, doctors can intervene early in the disease risk; in the future, cheaper, more accessible, higher quality medical care will Promoting machine learning algorithm technology has become mainstream, and it will also increase the requirements for doctors themselves.
Disease diagnosis is one of the more labor-intensive jobs in the medical system, and it is also the area of ​​expertise in machine learning algorithms. Although work in this area is still at an early stage of development, the technology is rapidly evolving and seems ready to be transformed into a “diagnostic medicineâ€.
With the increasing application of machine learning in the medical field, more and more machine learning applications have emerged in the case of medical diagnosis. Most diagnostic data is image-based, such as X-ray, magnetic resonance, and ultrasound images, as well as genome profiles, epidemiological data, blood tests, biopsy results, and even medical research papers. Therefore, this provides a large amount of data for training neural networks and other machine learning techniques.
Disease prediction: early detection and early treatment
Ordinary medical systems cannot always maintain accurate and rapid diagnosis, but machine learning not only cuts costs drastically, but diagnostic results are almost instantaneously available. In more and more cases, machine learning can provide a more accurate diagnosis than experienced doctors.
For example, a recent MIT Technology Review report pointed out that Hongyoon Choi and Hwan developed the Deep Convolutional Neural Network (CNN) at the Cheonan Public Health Center of Korea's Institute of Advanced Science and Technology and Kyong Hwan, which only passes PET (positron emission). The brain scan of the tomographic image can accurately determine whether the patient has a tendency to develop Alzheimer's disease within three years.
Hongyoon and Kyong used a brain image dataset of patients with mild cognitive impairment and developed Alzheimer's disease to predict the disease with an accuracy of 84%.
Early detection and early treatment are the key to reducing the cost of treatment for most diseases and even reversing the diagnosis.
In the case of Alzheimer's disease, it can delay the progression of the disease before the symptoms worsen. In the United States, Alzheimer's disease ranks sixth among the many causes of death. It is estimated that the cost of care for Alzheimer's in 2017 will reach $25.9 billion. This number is expected to soar to $1.1 trillion by 2050.
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