Integration of AI in Healthcare: Current Trends and Predictions 

Alina Zhanabayeva

September 3, 2023

It is considered that the incorporation of Artificial Intelligence (AI) within the healthcare field has brought about a significant change in the medical landscape. AI is moderately altering the way patients are cared for, how diagnoses and treatments are made, and how administrative tasks are handled, making healthcare work more efficient, precise, and accessible. The current trends in the integration of AI in healthcare and predictions for its future impact will be discussed in this article.

Firstly, AI-powered diagnostic tools have a sweeping effect on modern healthcare. Machine learning algorithms can analyze medical images, such as X-rays and MRIs, with remarkable accuracy, aiding in the early detection of diseases like cancer, cardiovascular conditions, and more. To illustrate, the AI called Linus Health is determined to modernize brain health through its cutting-edge cognitive assessment platform, prioritizing early detection.“Its proprietary assessment technology DCTclock takes the gold standard pen-and-paper clock drawing test for early signs of cognitive impairment and digitizes it, bringing together the most recent advances in neuroscience and AI to analyze over 50 metrics that reflect the patient’s cognitive function.” (Daley, 2018). These tools not only enhance diagnostic accuracy but also reduce the burden on healthcare professionals. 

Moreover, through the application of AI algorithms in the examination of extensive population data, it becomes possible to uncover trends and patterns that aid in forecasting the suitability of potential drug candidates for particular patient groups, therefore it can help tailor treatments to the needs of individual patients. “The potential of AI in the context of drug discovery has been demonstrated in several case studies. For example, the successful use of AI to identify novel compounds for the treatment of cancer has recently been reported by Gupta, R., et al. These authors trained a DL algorithm on a large dataset of known cancer-related compounds and their corresponding biological activity. As an output, novel compounds with high potential for future cancer treatment were obtained, demonstrating the ability of this method to discover new therapeutic candidates.” (Alexandre Blanco-González et al., 2023). 

On the other hand, there are some future predictions for AI like programming the ability to extract important information from a patient’s electronic footprint. “Take the example of a consultation with a patient with type 2 diabetes; currently a clinician spends significant time reading outpatient letters, checking blood tests, and finding clinical guidelines from a number of disconnected systems. In contrast, AI could automatically prepare the most important risks and actions given the patient’s clinical record. It could also automatically convert the recorded dialogue of the consultation into a summary letter for the clinician to approve or amend. Both of these applications would save considerable time and could be implemented very quickly because they assist clinicians rather than replacing them.” (Buch et al., 2018).

In addition, AI has shown potential in deciphering a variety of image data, such as retinal scans, radiographs, and ultrasound images. It is also noted that most of this imagery can be obtained using readily accessible and cost-effective equipment. Consequently, AI-based systems will bring specialist diagnostic expertise into primary care. For instance, “If an image of a skin lesion is sufficient to capably diagnose its aetiology, images could be captured at a GP practice and sent to a specialist dermatology AI system for instant analysis. Patients identified as low risk would receive instant reassurance while high-risk patients would experience lower referral waiting times because clinics would only be receiving selected cases.” (Buch et al., 2018).

In conclusion, as AI continues to advance and mature, its partnership with healthcare professionals promises to redefine the healthcare field. While AI brings efficiency and precision to the forefront, it is essential to address ethical, regulatory, and privacy concerns to ensure that AI in healthcare remains a force for positive change in the years to come. The future of healthcare is undoubtedly intertwined with the promise and potential of Artificial Intelligence.

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