Literature Survey and an Idea Comprehension on Prediction of Hysterectomy in Women Using Natural Language Processing and Deep Learning Technique for Electronic Health Record

• Published in: SN computer science 2023-05, Vol.4 (3), p.255, Article 255
• Main Authors: Kumar, Aishwarya N., Meenakshi Sundaram, A.
• Format: Article
• Language: English
• Subjects: Algorithms; Artificial intelligence; Chronic conditions; Computer Imaging; Computer Science; Computer Systems Organization and Communication Networks; Data base management systems; Data Structures and Information Theory; Deep learning; Disease; Electronic health records; Females; Health care; Hospitals; Hysterectomy; Information Systems and Communication Service; Language; Literature reviews; Medical records; Natural language processing; Patients; Pattern Recognition and Graphics; Physicians; Prediction models; Software Engineering/Programming and Operating Systems; Survey Article; Unstructured data; Uterus; Vision; Womens health
• ISSN: 2661-8907; 2662-995X; 2661-8907
• DOI: 10.1007/s42979-022-01597-w

Doctors today are facing humongous challenges in handling the non-electronic health record (EHR) especially in patients having chronic conditions which dates back to decades. Techniques of artificial intelligence and deep learning can be used to benefit the EHR by uplifting all its crucial aspects. It includes patient safety, good knowledge, effective and efficient usage of records, better understanding between doctor and a patient, early detection of disease, providing required medications in acute stages and providing better health care. There is a need to handle the multidimensional, unstructured raw data into structured, unidirectional data having only the vitals and eliminate the need of patient having to carry huge files every time they visit the doctor’s office. Long, unwanted and repeated data in the non-EHR which are of no importance needs to be eliminated which saves a lot of time for doctors, which can rather be used for better treatment in patients. The predictions of possible occurrence of benign conditions with respect to hysterectomy in female is extracted from the non-EHR along with other salient data is collected in the form of questionnaire. Early medications, life-style changes can be advised to patients with high probability of having to go through hysterectomy in future is predicted, which can be life-saving. Prominent concepts in the field of Artificial intelligence like natural language processing and Prediction models can be used to attain the desired outcomes. On the bigger canvas, the same technique can be implemented in every health care system of various fields of medicine for patients with chronic conditions having numerous diseases.