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Implications of AI on Cardiovascular Patients’ Routine Monitoring and Telemedicine Arbaz Haider Khan; Hira Zainab; Roman Khan; Hafiz Khawar Hussain
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 5 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Cardiovascular and chronic disease management and treatment are started to incorporate Artificial Intelligence gradually into cardiovascular telemedicine and remote monitoring. Through the use of AI technologies, patients are much benefited, and at the same time, it promotes improvement in patients, examination, and continuous monitoring. Since the use of AI forefront in its role as a monitoring technique, predictive analytics, risk factors and detail personal medication in zone of cardio vascular diseases, this paper dwells on one how cardio vascular care is evolving with experimental use of AI. It also describes the limitation and challenge of AI use, for instance, around data privacy, legal regime and data quality, and AI moral decisions such as the disposition of openness and trust. Nevertheless, the current demands require future development in cardiology –telemedicine with the use of artificial intelligence in prescriptive and predictive cardiology based on precision medicine, machine learning, and genomic as well as electronic health records data. Therefore, the following aspects should be addressed to overcome the present challenges to the effective functioning of AI in the healthcare segment of cybersecurity threats, data connections, and accessibility. Therefore, the paper’s conclusion about the subject AI obversive points to the potential for a full-scale revolution in the sphere of cardiovascular care with regards to the patient’s outcomes and accessibility and effectiveness on the international level under conditions of further regulation as well as technological enhancement.

Integration of AI and Wearable Devices for Continuous Cardiac Health Monitoring Hira Zainab; Arbaz Haider Khan; Roman Khan; Hafiz Khawar Hussain
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.4956

The all-new integrative and wearable technology and AI universal steady cardiac health checkup will redefine the entire concept of cardiovascular treatment where checkup-detection-diagnosis of diseases will be done at early stage, followed by targeted therapy in real time. In as much as pertains the improvement of cardiac health results, this paper presents the prospects and threats associated with the integration of wearable devices such as heart rate monitor, ECG and other similar devices with AI algorithms. It also means that benchmarks that result from processing data from wearable’s can be established for AI systems in order to predict outcomes and consequently develop better care plans for ordinary patients. However, as of now, there are definite some certain ethically legally, and policy relevant concern with these technologies. Most is do with data ownership and privacy as well as understanding and obtaining the patients consent, dealing with the bias issue in regards to artificial intelligence basic decision making and ensuring explicit accountability and transparency throughout the process. Still to encourage innovation, and more mixing of smart wearable’s and artificial intelligence, it means that the requirements have to be adaptive to guarantee safety without necessarily denting the set effectiveness. Another shift that has to occur in reimbursement structures is that the various new technologies have to be made available for use and, therefore, appropriate reimbursement structures for them has to be promoted. In addition, the assessment equally applauds that for AI to complement rather than supplant human discretion, the balance of maintaining, on the one hand, the doctor-patient relationship and, on the other hand, the technical should be achieved. After comparing the major concepts of both the wearable technology and the artificial intelligence, the two would revolutionaries the monitoring of cardiac health. However, success in the outgoing needs such important aspects as access, ethical and legal question to monitor the position that the achieved success does not deepen health inequality.

Advances in Predictive Modeling: The Role of Artificial Intelligence in Monitoring Blood Lactate Levels Post-Cardiac Surgery Roman Khan; Hira Zainab; Arbaz Haider Khan; Hafiz Khawar Hussain
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.4957

Total blood lactate levels monitoring through the use of Artificial Intelligence in individuals that have undergone cardio surgeries is a milestone in critical care because it indicates metabolic problems earlier than traditional approaches. Lactate levels have to be significantly raised in order they may indicate complications like tissue hypoxia, sepsis or organ dysfunction. The previous method of monitoring lactate entails conducting tests after a few hours or days and can be very unresponsive; in the application of AI models, the algorithm scans through data acquired from patient monitoring systems to predict and advance notice the clinicians on the trends in lactate levels. This review outlines the basic mechanisms, algorithms, and features required to build an AI-based lactate predictor and the multiple physiologic signals such as heart rate, oxygen saturation, and blood pressure into the support vector regression model. Illustrative cases show that AI can facilitate more effective clinical decision-making to increase ICU patient safety and decrease such hospital stays. While AI based lactate tracking is something that has been bandied about in the research literature for some time, there are real questions as to how this is implemented in existing hospitals, how one minimizes the negative impacts of alarm fatigue, and how the results are persistent across population groups. Ethical and legal necessities concerning patient’s data confidentiality, security, and further reporting also play the vital role of its clinical endorsement. Other directions for future work are more flexible and multiple modality models that include additional data and require learning from new patient data.

Integration of AI and Wearable Devices for Continuous Cardiac Health Monitoring Hira Zainab; Arbaz Haider Khan; Roman Khan; Hafiz Khawar Hussain
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.4956

The all-new integrative and wearable technology and AI universal steady cardiac health checkup will redefine the entire concept of cardiovascular treatment where checkup-detection-diagnosis of diseases will be done at early stage, followed by targeted therapy in real time. In as much as pertains the improvement of cardiac health results, this paper presents the prospects and threats associated with the integration of wearable devices such as heart rate monitor, ECG and other similar devices with AI algorithms. It also means that benchmarks that result from processing data from wearable’s can be established for AI systems in order to predict outcomes and consequently develop better care plans for ordinary patients. However, as of now, there are definite some certain ethically legally, and policy relevant concern with these technologies. Most is do with data ownership and privacy as well as understanding and obtaining the patients consent, dealing with the bias issue in regards to artificial intelligence basic decision making and ensuring explicit accountability and transparency throughout the process. Still to encourage innovation, and more mixing of smart wearable’s and artificial intelligence, it means that the requirements have to be adaptive to guarantee safety without necessarily denting the set effectiveness. Another shift that has to occur in reimbursement structures is that the various new technologies have to be made available for use and, therefore, appropriate reimbursement structures for them has to be promoted. In addition, the assessment equally applauds that for AI to complement rather than supplant human discretion, the balance of maintaining, on the one hand, the doctor-patient relationship and, on the other hand, the technical should be achieved. After comparing the major concepts of both the wearable technology and the artificial intelligence, the two would revolutionaries the monitoring of cardiac health. However, success in the outgoing needs such important aspects as access, ethical and legal question to monitor the position that the achieved success does not deepen health inequality.

Advances in Predictive Modeling: The Role of Artificial Intelligence in Monitoring Blood Lactate Levels Post-Cardiac Surgery Roman Khan; Hira Zainab; Arbaz Haider Khan; Hafiz Khawar Hussain
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.4957

Total blood lactate levels monitoring through the use of Artificial Intelligence in individuals that have undergone cardio surgeries is a milestone in critical care because it indicates metabolic problems earlier than traditional approaches. Lactate levels have to be significantly raised in order they may indicate complications like tissue hypoxia, sepsis or organ dysfunction. The previous method of monitoring lactate entails conducting tests after a few hours or days and can be very unresponsive; in the application of AI models, the algorithm scans through data acquired from patient monitoring systems to predict and advance notice the clinicians on the trends in lactate levels. This review outlines the basic mechanisms, algorithms, and features required to build an AI-based lactate predictor and the multiple physiologic signals such as heart rate, oxygen saturation, and blood pressure into the support vector regression model. Illustrative cases show that AI can facilitate more effective clinical decision-making to increase ICU patient safety and decrease such hospital stays. While AI based lactate tracking is something that has been bandied about in the research literature for some time, there are real questions as to how this is implemented in existing hospitals, how one minimizes the negative impacts of alarm fatigue, and how the results are persistent across population groups. Ethical and legal necessities concerning patient’s data confidentiality, security, and further reporting also play the vital role of its clinical endorsement. Other directions for future work are more flexible and multiple modality models that include additional data and require learning from new patient data.

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