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The use of data has become highly prevalent in various fields today. Data enables policymakers to make decisions objectively and efficiently. Similarly, in medicine, data simplifies the diagnosis of patients and the follow-up care based on patient history. Implementing data into healthcare will enhance personalised patient care to achieve satisfaction.
Khon Kaen University recognises its crucial role in academic research and academia. Recently, in collaboration with several departments, including the Faculty of Medicine, Faculty of Engineering, College of Computing, KKU Academy, KKU Library, Office of Teaching and Learning Innovation, and a network of Medical Faculties from Ramathibodi Hospital, Mahidol University, clinical research, and traded commercial bank in Thailand have embarked on organised a training regarding data comprehension which Professor Mengling’ Mornin’ Feng led.
According to Assoc Prof Sirapat Chiawchanwatana, PhD, who serves as the Dean of the College of Computing, Thailand’s healthcare system is considered a model for many nations. Thailand possesses valuable health data recorded within its healthcare service system and ongoing health research efforts. However, there are limitations regarding the data system’s comprehensiveness and utilisation to address healthcare system challenges. Therefore, this presents an opportunity to establish the Datathon Competition in Thailand.
“Khon Kaen University has previously worked together with Prof Mengling’ Mornin’ Feng. This provides a valuable opportunity to establish a network of experts in health data and AI within the community, fostering collaboration in the implementation of Health AI initiatives for the maximum benefit of the population,” expressed Assoc Prof Sirapat Chiawchanwatana.
The efforts undertaken by Khon Kaen University represent a noteworthy contribution towards advancing and transforming the healthcare community within the academic sphere, fostering greater data literacy in Thailand. Additionally, embracing data integration in healthcare offers numerous advantages, and one of the most prominent ones is the precision it brings to the diagnostic process.
For instance, recent research conducted by a collaborative team comprising the National Metal and Materials Technology Centre (MTEC), the National Science and Technology Development Agency (NSTDA), the Department of Radiology at the Faculty of Medicine, Ramathibodi Hospital, and an engineering and technical service company has unveiled significant advancements in breast cancer detection and prediction.
Their groundbreaking achievement includes the development of a breast simulation platform meticulously designed to enhance the proficiency of medical professionals in conducting ultrasound-guided breast biopsies. This platform offers an immersive learning experience, providing realistic data imaging and needle procedures. It aims to empower healthcare practitioners to deliver more precise diagnoses while reducing their reliance on imported training equipment by analysing the data.
Its design emphasises reusability by erasing needle marks after each session, promoting sustainability and cost-effective training for medical professionals. It ensures repeated practice opportunities and reduces the need for excessive resources.
Integrating real-time feedback and adjustable difficulty levels further tailors the learning experience, accommodating learners at various stages of expertise. By bridging the gap between theoretical knowledge and hands-on proficiency, the breast simulation platform plays a pivotal role in shaping confident and competent practitioners in the field of breast diagnostics.
In light of the advancement of data utilisation in healthcare, the convergence of innovative solutions with the expertise of healthcare professionals will usher in a new era of medical excellence. This cutting-edge technology and the knowledge and skills of healthcare practitioners promise to redefine patient care and healthcare practices.
By embracing data configuration, healthcare professionals can harness the power of data analytics and machine learning to enhance diagnostic precision and streamline patient care processes. The accessibility of medical information has become more efficient, enabling quicker and more informed decision-making.