A new era of healthcare is being ushered in by generative AI, which has profound effects on patient care, diagnostics, and other areas. Will technology contribute to democratizing access to healthcare for all and helping to solve some of the most pressing issues plaguing our overburdened healthcare systems? Based on these examples, it is clear that generative AI can significantly improve the healthcare industry.
These are the top six ways that generative AI can enhance the provision of healthcare:
- Tailored On-Demand Medical Advice
A new generation of virtual health aids has resulted from the combination of human medical competence and sophisticated generative AI models, such as GPT-4. Ada is an AI-powered software created by doctors that can evaluate symptoms and provide users with medical advice in a variety of languages, including English, German, French, Spanish, Portuguese, and Swahili. Thirteen million people have downloaded the app to date, and over thirty million symptom assessments have been done. It asks you questions about your symptoms (you can make individual symptom profiles for family members as well), and it then directs you to resources for medical advice and potential diseases. Your symptoms are also tracked by the app as they worsen.
We may anticipate generative AI to take up some of the slack, as millions of people worldwide lack access to healthcare due to a variety of factors, including geography, finances, or overstretched local systems.
- Expert Medical Care From Busy Physicians
Generative AI systems, which operate in the background, listen, take notes, and generate possible questions for the doctor to ask based on the patient’s history and symptoms, are something I think we’ll see more and more of during doctor-patient consultations. It would resemble a hybrid of a diagnostic tool and a medical chatbot, intended for one-on-one patient consultations.
A wonderful example is provided by RythmX AI, which has developed a precision care platform to assist physicians in providing hyper-individualized treatment. Essentially, the system provides recommendations and actions tailored to the individual patient through the application of generative and predictive AI algorithms. Physicians can further explore the suggestions through the natural language interface, making it akin to an AI assistant for medical professionals. Doctors may be able to maximize patient appointments with the aid of this kind of AI-augmented method (which can be as quick as 10 minutes).
- Customised Treatment and Health Plans
By evaluating large patient datasets to suggest individualized treatment regimens, optimize medicine dosages, and anticipate possible bad effects, generative AI may also assist physicians in improving patient care. Additionally, it can help with the development of customized therapy and rehabilitation routines.
Furthermore, preventative medicine may benefit from the application of generative AI. Regenerative AI, for instance, might be used by clinics and hospitals to develop individualized treatment programs based on each patient’s particular genetic composition, medical history, and lifestyle.
- Image Analysis and Early Disease Detection
While AI has long been present in diagnostics, the analysis of medical images will be much improved by generative AI. As a result, generative AI technologies will be utilized more frequently to assist radiologists in quickly and accurately diagnosing diseases using X-rays, MRIs, and CT scans.
In one study, the use of AI to produce radiograph reports and analyze chest radiographs in the emergency room was investigated. Images are frequently evaluated by a remote radiologist (referred to as “teleradiology”) or even by emergency room physicians because many emergency departments lack 24/7 access to specialized radiology services. According to the study, the AI tool produced quick interpretations of radiographs and reports that were as accurate and high-quality as those written by radiologists, if not higher. In one instance, the AI outperformed a human radiologist in identifying a problem that the radiologist neglected to report. This demonstrates that AI can assist doctors in various departments in interpreting medical pictures and expediting patient processing, in addition to helping radiologists complete their work more rapidly and efficiently.
- Boosting Drug Development
Generative AI is already making an influence on the development of novel pharmaceuticals to treat ailments. How? In other words, technology can make it easier for researchers to comprehend disease signals and identify the best chemical combinations—or even completely construct new ones—to develop novel pharmaceutical treatments. Therefore, through the creation of new chemical structures, quick compound screening, prediction of drug interactions, repurposing of current medications for new uses, optimization of clinical trials, and improvement of drug formulations, generative AI will hasten the process of drug discovery and development.
Because medications might potentially be customized based on unique patient data, this could potentially improve individualized treatment in the future.
- Improvements Made Behind The Scenes in Healthcare Environments
Generative AI can lessen the administrative load in healthcare settings, especially by automating routine queries, note-taking, medical coding, and invoicing. This may not sound as exciting as finding new treatments or enabling tailored care. When you take into account the jobs that generative AI can perform—writing, listening, translating spoken language, and text comprehension—it all makes a lot of sense.
The Ambient Assist note-taking tool from NextGen Healthcare, which listens to patient-provider talks and then generates summary notes, is a nice example. After the patient contact, the notes are ready for the physician to examine in only 30 seconds, and the tool accurately records appointments with over 90%. Thus, NextGen and similar products assist clinicians in reducing administrative workloads without sacrificing clinical documentation. Anything that might reduce the administrative burden on physicians could have a huge positive impact on our healthcare systems since it is one of the main causes of clinician burnout.
Having excellent care from medical experts who are people who cannot be replaced. However, generative AI provides options that can aid in bridging the gap between the seemingly diminishing healthcare resources and the expanding need for healthcare. Combining human and machine expertise will probably be the most effective way to identify patients and administer the right treatment as healthcare systems grow increasingly overburdened.
