RESEARCH ON THE APPLICATION OF SAP’S AI AND MACHINE LEARNING SOLUTIONS IN DIAGNOSING DISEASES AND SUGGESTING TREATMENT PROTOCOLS

Abstract

The focus of this paper is to determine how the various AI and machine learning modules of SAP are revolutionizing the diagnosis and treatment of diseases in the healthcare sector. The incorporation of AI and ML components within the SAP systems has been a major step forward in using this technology in healthcare sectors mostly in the diagnosis and management of diseases. SAP solutions that use AI can improve its capacity for analyzing large volumes of data and accurately seeking out relationships and tendencies that might be beyond human clinicians’ discernment. Applying the described insights, AI modules within SAP can help identify diseases at their initial stage, forecast the further development of diseases, and offer individualised treatment based on the patent’s characteristics [1]. This facilitates the accurate identification of ailments that patients have, as well as adjustment of treatment schedules and delivery in a way that will leave patients with optimum results. SAP’s digital solutions for AI and ML are embedded seamlessly in the current structures of healthcare systems and offer real time analysis/ decision support systems to assist clinicians in decision making. These systems use complex analytics that include medical records, imaging data, and genetic information to convert data into insight. For example, in the case of cancer, SAP’s AI can identify the outcome that portrays the specific tumor and even the genetics wheel to suggest the right chemotherapy regimen. Likewise in chronic illness care, the system can track a patient's health status, and offer changes to therapy regimens to keep patients in the best of health possible [1]. The analysis of AI and machine learning in SAP for the healthcare industry revealed the possibility of reshaping healthcare with higher accuracy in diagnosis and more precise treatment plans. Through the accumulation of data, these AI systems improve their patterns in the disease thereby improving the disease control plans. Besides, this also makes the burden from the healthcare provider’s side lighter and helps the patient to be more positive and proactive with the kind of treatment that they are preparing to undergo or are going through. Thus, continuous updates are necessary where improvements and innovative solutions are sought after in order to promote its use and efficient incorporation into globalized health care systems which would lead to a better performing health care system.