• Sindhu Rajendran
• Dr. Chandrashekar B S

The integration of artificial intelligence and machine learning (AIML) in telemedicine has revolutionized the healthcare industry by providing innovative solutions to improve patient care and clinical processes. The paper aims to delve into the application of AIML algorithms in telemedicine, particularly focusing on their role in summarizing clinical conversations and generating required prescriptions. The paper begins by providing an overview of the current landscape of telemedicine and the challenges associated with remote patient care, including the need for accurate and efficient clinical conversation summarization and prescription generation. Subsequently, it explores the various AIML techniques and algorithms that have been developed to address these challenges, emphasizing their potential to enhance the quality of telemedicine services. Furthermore, the review discusses the utilization of natural language processing (NLP) algorithms for extracting essential information from clinical conversations, such as patient symptoms, medical history, and diagnostic findings. It highlights the significance of NLP in converting unstructured clinical data into structured formats, thereby enabling the generation of comprehensive and concise summaries that facilitate informed decision-making by healthcare providers. In addition, the paper delves into the advancements in machine learning models for prescription generation, emphasizing the importance of personalized medicine and adherence to clinical guidelines. It elucidates how AIML algorithms can analyze patient data, medical records, and evidence-based practices to recommend appropriate treatment regimens and medications, taking into account individual patient characteristics and medical history. Moreover, the review addresses the ethical and legal considerations associated with the use of AIML in telemedicine, emphasizing the importance of data privacy, algorithm transparency, and informed consent. It also explores the potential benefits and challenges of integrating AIML-powered clinical conversation summarization and prescription generation tools into existing telemedicine platforms, highlighting the need for rigorous evaluation and validation of these technologies. Overall, the paper aims to provide a comprehensive understanding of the role of AIML in telemedicine, specifically focusing on algorithms for summarizing clinical conversations and generating required prescriptions. By critically analyzing the current state of research and development in this domain, the paper aims to shed light on the opportunities, challenges, and future directions for leveraging AIML to enhance telemedicine services and improve patient outcomes.

Artificial Intelligence, Machine learning, Telemedicine, Health, Medical sector

"A Review on medical prescriptions using advanced technology in Telemedicine", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 7, page no.f391-f395, July-2024, Available :http://www.jetir.org/papers/JETIR2407555.pdf

"A Review on medical prescriptions using advanced technology in Telemedicine", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 7, page no. ppf391-f395, July-2024, Available at : http://www.jetir.org/papers/JETIR2407555.pdf