The use of Artificial Intelligence has many benefits for healthcare. Consider, for example, faster diagnoses, accurate treatments and better informed patients. AI often seems far away; it is seen as something for the future. The investment is too large and the result too uncertain. However, AI has not been a future for some time, but today's reality. Currently, technology is already being used in various ways to improve healthcare. In this blog we show you six successful examples of AI in healthcare.
Data management for better research and a better treatment method
To begin with, there is the Deepmind Health Project from Google. This project focuses on deep learning. In deep learning, algorithms explain patients' head, neck and eye scans. The system learns how to detect irregularities in the scans. The system then advises the treating physician about potential treatments. The system supports and advises the physician in establishing a diagnosis for the patient. This reduces the chance of a wrong diagnosis.
Virtual assistant for analyzing visual material
IBM is involved in the development of an algorithm for radiologists and cardiologists. With this algorithm, echoes and scans are interpreted more thoroughly and faster. This allows specialists to spend more time on complicated cases. The algorithm does not count as a doctor's replacement. It supports the physician in analyzing the information from the scans and drawing conclusions based on this data.
An app that compares health complaints with disorders
Babylon Health : Online Doctor Consultations & Advice is developing an app. With this app, people use speech recognition to indicate which health problems they are experiencing. This app then compares the complaints with disorders in the database. The application then makes a proposal for taking the next steps. This proposal is based on the medical information from the database and the medical history of the patient. The app does not make a certain diagnosis, but shows the patient what the symptoms could mean. It is then up to the patient to decide whether or not to visit a doctor based on this information.
The Molly App is an app that serves as a virtual nurse. The Molly App has a pleasant voice and a friendly face. The app uses machine learning and supports the chronically ill in between doctor's visits. The app monitors the condition of the patient and checks whether the treatment is successful. The Molly App mainly serves as a measuring instrument and as a means to give the patient more confidence in daily life.
Manufacturer of genetic medicines Deep Genomics has developed a platform for precision medicine. This platform is able to identify large amounts of medical data, patterns of genetic information, mutations and indications for diseases. Doctors gain insight into what happens in a cell when the DNA changes. This is usually the result of a genetic variation (this can occur both naturally and through treatment). The platform therefore contributes to the early detection of changes in DNA and maps out how this process works.
Rapid development of new medicines
The supercomputers of molecule designer Atomwise use a database with molecular profiles. This has enabled the company to reduce the contagiousness of Ebola in a short time. This result has been achieved by combining two existing medicines. The aim of Atomwise is to make discoveries with which partner companies in the pharmaceutical industry can quickly develop better medicines. They do this by combining existing medicines and developing new molecules.
Points of attention when applying AI in healthcare
Artificial intelligence promises many possibilities for the future. Nevertheless, it is important to take a number of points into account. Ethical standards must be taken into account when carefully introducing AI into healthcare. The introduction must also take place gradually, so that patients can gradually get used to AI. In addition, with a gradual introduction, any problems can be tackled quickly.
Healthcare professionals need to know what they are doing when they integrate AI into their work. It is therefore important that they gain knowledge about applying AI in a medical environment. AI-developing organizations must in turn communicate well about the pros and cons of AI in health care.
Source: Inter SystemsAI, gezondheid, Kunstmatige intelligentie, medisch, zorg