Combining big data and deep learning is a world-shattering technology that can significantly impact any objective if appropriately used. With a large volume of available healthcare datasets and progressions in deep learning techniques, systems are now well-equipped to predict the future trend of any health problems. From the literature survey, we found that the SVM was used to predict the heart failure rate without relating objective factors. Utilizing the intensity of important historical information in electronic health records (EHR), we have built a smart and predictive model utilizing long short-term memory (LSTM) and incorporating correlation between clinical variables. Hence, the fundamental commitment of this work is to predict the failure of the heart using an LSTM based on the patient’s electronic medicinal information. We have analyzed a dataset containing the medical records of 299 heart failure patients collected at the Faisalabad Institute of Cardiology and the Allied Hospital in Faisalabad (Punjab, Pakistan). We have found an increasing trend in our analysis which will contribute to advancing the knowledge in the field of heart stroke prediction.
Original languageEnglish
Title of host publication2023 International Conference on Digital Image Computing
Subtitle of host publicationTechniques and Applications (DICTA)
Place of PublicationUnited States
Number of pages8
ISBN (Electronic)9798350382204
ISBN (Print)9798350382211 (Print on demand)
Publication statusPublished - 2023
EventThe International Conference on Digital Image Computing: Techniques and Applications: DICTA 2023 - Sails Port Macquarie, Port Macquarie, Australia
Duration: 28 Nov 202301 Dec 2023
https://www.dictaconference.org/?page_id=2623 (Conference program)


ConferenceThe International Conference on Digital Image Computing: Techniques and Applications
CityPort Macquarie
OtherDigital Image Computing: Techniques and Applications (DICTA) is the main Australian Conference on computer vision, image processing, pattern recognition, and related areas. DICTA was established in 1991 as the premier conference of the Australian Pattern Recognition Society (APRS).
DICTA provides a forum for researchers, engineers, and practitioners to present their latest findings and innovations in these areas, as well as to exchange ideas and discuss emerging trends and challenges in the field. The conference covers a wide range of topics, including image and video processing, machine learning, pattern recognition, and computer graphics, among others.​
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