In India, the initial medical consultation typically lasts around 5 minutes, during which doctors inquire about the patient’s current medical history, conduct a physical examination, and recommend possible treatments. A comprehensive personal history is crucial for an accurate initial diagnosis. however, the brevity of these consultations can often result in misunderstandings regarding the patient’s needs, potentially leading to missed diagnoses. To address this, some clinics utilize pre-consultation surveys to gather detailed information, especially from patients beginning a new treatment. These surveys may include questions about significant medical histories, allergies, or prior conditions, although they are not always common or suitably comprehensive. It is possible to streamline the process and improve the quality of care by using digital tools to document a patient’s full medical history before the consultation. These tools have the potential to enhance efficiency by reducing data collection time and improving the accuracy of the information gathered. however, it is essential to tailor these tools to different user groups, considering factors, such as age, gender, and health literacy, to ensure the collection of reliable data. While some small studies have demonstrated the benefits of these digital tools, there is still a lack of comprehensive research, particularly across diverse patient populations. This study aims to explore the use of digital tools in recording clinical histories based on 39 common symptoms, with the goal of improving diagnostic accuracy and overall patient care

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Predictive Disease Modeling with Patient Medical Data History Using Machine Learning

  • Laith H. Alzubaidi

摘要

In India, the initial medical consultation typically lasts around 5 minutes, during which doctors inquire about the patient’s current medical history, conduct a physical examination, and recommend possible treatments. A comprehensive personal history is crucial for an accurate initial diagnosis. however, the brevity of these consultations can often result in misunderstandings regarding the patient’s needs, potentially leading to missed diagnoses. To address this, some clinics utilize pre-consultation surveys to gather detailed information, especially from patients beginning a new treatment. These surveys may include questions about significant medical histories, allergies, or prior conditions, although they are not always common or suitably comprehensive. It is possible to streamline the process and improve the quality of care by using digital tools to document a patient’s full medical history before the consultation. These tools have the potential to enhance efficiency by reducing data collection time and improving the accuracy of the information gathered. however, it is essential to tailor these tools to different user groups, considering factors, such as age, gender, and health literacy, to ensure the collection of reliable data. While some small studies have demonstrated the benefits of these digital tools, there is still a lack of comprehensive research, particularly across diverse patient populations. This study aims to explore the use of digital tools in recording clinical histories based on 39 common symptoms, with the goal of improving diagnostic accuracy and overall patient care