Uses of AI in the medical field - 0 views
started by ai_ar_services on 08 Feb 22
started by ai_ar_services on 08 Feb 22
started by ai_ar_services on 08 Feb 22
started by ai_ar_services on 08 Feb 22
Uses of AI in the medical field
Artificial intelligence, in itself, is rooted in the fact that it can perform and simulate human-level intelligence with the arithmetic capabilities of a machine which makes it essential in critical fields such as medicine. Its use in this field is dichotomized into two sub-types: Virtual and Physical. The virtual part ranges from applications such as electronic health record systems to neural network-based guidance in treatment decisions, while the physical part deals with robots assisting in performing surgeries, intelligent prostheses for handicapped people, and elderly care. The aforementioned neural networks used in the virtual part are essentially a series of processors acting as neurons to analyze complex statistical data. This provides valuable insight into the key use of AI in the medical field as we can now gauge the importance that this analysis might play in recognizing symptom patterns in patients to provide a more complete and foolproof diagnosis as compared to a doctor. These neural networks learn the art of diagnosing a patient via two broad techniques, namely, the flowchart approach and the database approach.
Uses of AI in the medical field
The flowchart-based approach involves translating the process of history-taking, i.e., a physician asking a series of questions and then arriving at a probable diagnosis, by combining the symptom complex presented. Conversely, the database approach utilizes the principle of deep learning or pattern recognition that involves teaching a computer via repetitive algorithms in recognizing what certain groups of symptoms or certain clinical/radiological images look like. But it is useful to note that, the flowchart approach requires feeding large amounts of data into machine-based cloud networks considering a wide range of symptoms and disease processes encountered in routine medical practice. Therefore, the outcomes of this approach are limited because the machines are not able to observe and gather cues that can only be observed by a doctor during the patient encounter. While on the other hand, the database system is trained to recognize images based on over 10 million YouTube videos with its efficiency only improving after each view, allowing it to predict symptoms with over 75 percent accuracy, after only 3 days of learning. The key summary from this analysis of the effectiveness of AI is that it has been proven to be a failproof and fast solution to a large number of problems encountered in the medical field and is therefore used abundantly in the industry.
Uses of AI in the medical field
A few noteworthy examples of AI being utilized in the medical field are seen to be ranging from online scheduling of appointments, online check-ins in medical centers, digitization of medical records, reminder call for follow-up appointments, and immunization rates for children and pregnant females to drug dosage algorithms and adverse effect warnings while prescribing multidrug combinations. Radiology is the branch that has been the most upfront and welcoming to the use of this new AI technology. Computers being initially used in clinical imaging for administrative work like image acquisition and storage are now becoming an indispensable component of the work environment with the origin of picture archiving and communication systems. The decision support system is also another crucial example in pioneering the use of AI technology in medicine, this decision support system, or DXplain, was developed by the University of Massachusetts in 1986, which gives a list of probable differentials based on the symptom complex and it is also used as an educational tool for medical students filling the gaps not explained in standard textbooks. In addition to this, applications like Germwatcher, a system developed by the University of Washington to detect and investigate hospital-acquired infections; Babylon, An online application in the UK used by the patients to consult the doctor online, check for symptoms, get advice, monitor their health, and order test kits, and AI-therapy, an online course that helps patients treat their social anxiety are all primary examples of the mass use of AI in the field.
Uses of AI in the medical field
The other enormous pillar in the use of AI in the medical industry is the use of AI in hands in the dirt surgery where robotics and AI are partnered to provide a more precise and safe operation than most humans are capable of accomplishing. The DA Vinci robotics surgical system developed by intuitive surgical, plays the leading role in this sector of the medical field, especially in urological and gynecological surgeries. The robotic arm of the system mimics a surgeon's hand movements with better precision and has a 3D view and magnification options that allow the surgeon to perform minute incisions. In conclusion, we can see that AI is growing into the public health sector and is going to have a major impact on every aspect of primary care. AI-enabled computer applications will help primary care physicians to better identify patients who require extra attention and provide personalized protocols for each individual. Primary care physicians can use AI to take their notes, analyze their discussions with patients, and enter required information directly into EHR systems. These applications will collect and analyze patient data and present it to primary care physicians right alongside insight into patients' medical needs proving to be an important and necessary partner for all doctors now in the twenty-first century.