Modern Medical Laboratory Journal

The use of artificial intelligence (AI) has been enabled by the use of labeled big data, along with markedly enhanced computing power and cloud storage, across all sectors. In medicine, this is beginning to have an impact at three levels: for clinicians, predominantly via rapid, accurate image interpretation; for health systems, by improving workflow and the potential for reducing medical errors; and for patients, by enabling them to process their own data to promote health. The current limitations, including bias, privacy and security, and lack of transparency, along with the future directions of these applications will be discussed in this article. Over time, marked improvements in accuracy, productivity, and workflow will likely be actualized, but whether that will be used to improve the patient–doctor relationship or facilitate its erosion remains to be seen.
Recently, the release of ChatGPT, the latest large (175-billion-parameter) language model by San Francisco-based company OpenAI, prompted many to think about the exciting (and troublesome) ways artificial intelligence (AI) might change our lives in the very near future. AI has a tremendous potential to revolutionize health care and make it more efficient by improving diagnostics, detecting medical errors, and reducing the burden of paperwork. 

Here are some examples of the use of AI in medicine:

1. Diagnostic support:  AI algorithms have been used to assist in the diagnosis of skin cancer, heart disease, and eye diseases.

2. Predictive analytics: AI can be used to analyze vast amounts of patient data to predict future health problems and help healthcare professionals to intervene early.

3. Personalized medicine: AI can be used to analyze individual patient data to create personalized treatment plans and improve patient outcomes.

4. Imaging analysis: AI algorithms have been developed to assist in the interpretation of medical images, such as X-rays, CT scans, and MRI scans.

5. Drug discovery: AI can be used to analyze large amounts of data from clinical trials to speed up the drug development process and increase the chances of success for new treatments.

6. Telemedicine: AI can be used to support remote patient consultations and improve access to healthcare in remote and underserved areas.

7. Surgical support: AI can be used to assist in surgical procedures, such as guiding surgical instruments and providing real-time feedback during the procedure.

These are just a few examples of the use of AI in medicine. The field is constantly evolving, and new AI applications are being developed all the time.
Read more