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Advancements in Detection and Mitigation: Fortifying Against APTs - A Comprehensive Review Aashesh Kumar; Muhammad Fahad; Haroon Arif; Hafiz Khawar Hussain
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 1 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Organizations' cyber security posture is severely challenged by Advanced Persistent Threats (APTs), necessitating a multifaceted defense strategy. Traditional methods, machine learning, artificial intelligence (AI), behavioral analytics, real-time monitoring, incident response, collaborative defense mechanisms, endpoint security enhancements, network segmentation and access control, encryption, data protection, and user training and awareness are just a few of the strategies and advancements in APT detection and mitigation that are examined in this review article. Every tactic is thoroughly reviewed, emphasizing its value in thwarting APT attacks and offering best practices for execution. By utilizing these cutting-edge methods and encouraging cooperation amongst enterprises, it is feasible to improve defenses against APTs and lessen the likelihood that they will affect vital assets and data.

Transforming Healthcare: The Dual Impact of Artificial Intelligence on Vaccines and Patient Care Abdul Mannan Khan Sherani; Muhammad Umer Qayyum; Murad Khan; Ashish Shiwlani; Hafiz Khawar Hussain
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 2 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Artificial intelligence (AI) has the potential to transform healthcare and immunization programs, enhance patient outcomes, and advance public health goals. This can be achieved by the incorporation of AI into these tactics. This study examines the complex effects of AI on vaccine distribution, development, efficacy tracking, personalized medicine, and fair access to healthcare. AI-driven methods speed up the development of vaccines by identifying candidates more quickly, improving the design of formulations, and making unprecedentedly accurate and fast predictions about their efficacy. Furthermore, AI improves supply chain management and vaccine distribution by streamlining scheduling, routing, and allocation procedures to provide fair access for all populations. By using AI to customize vaccination regimens based on unique traits, preferences, and risk profiles, personalized medicine techniques increase immunization efficacy and reduce side effects. In addition, AI reduces healthcare disparities by highlighting interventions for underrepresented groups, identifying underprivileged communities, reducing biases, and enhancing transparency. While AI has the potential to be a game-changer, in order to maintain moral standards and advance fair access to healthcare services, ethical issues like privacy, prejudice, transparency, and equity must be carefully considered. All things considered, the incorporation of AI into immunization programs and healthcare signifies a paradigm change that could help to mold a future in which everyone has access to more effective, equitable, and individualized healthcare.

Green Innovations: Artificial Intelligence and Sustainable Materials in Production Shahrukh Khan Lodhi; Ahmad Yousaf Gill; Hafiz Khawar Hussain
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 4 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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This study examines the revolutionary potential of integrating artificial intelligence (AI) with sustainable materials in production through a series of case studies, featuring innovations by Adidas, Tesla, Unilever, and IKEA. These illustrations demonstrate how AI may be used to create recyclable goods, maximize material efficiency, and simplify supply chains—all of which greatly lessen the manufacturing process's negative environmental effects. The study also identifies the main domains in which these technologies are propelling improvements in operational effectiveness and environmental sustainability. Robust regulatory frameworks are required to assure the safe, transparent, and equitable implementation of AI as it becomes increasingly integrated into industrial processes. The article also highlights the need for responsible innovation by discussing the ethical and policy ramifications of utilizing AI in sustainable manufacturing, as well as the societal impact of AI on data privacy and the workforce. Lastly, the environmental effects of AI itself are discussed, emphasizing the need for renewable energy sources and energy-efficient AI systems. Through collaboration between governmental, industrial, and social sectors, artificial intelligence (AI) can be leveraged to propel environmentally and socially responsible production methods. In order to create a more sustainable and prosperous future, the paper's conclusion emphasizes the need for a balanced strategy that optimizes AI's benefits while guaranteeing moral and egalitarian outcomes. Going ahead, the report makes the case that artificial intelligence and sustainable materials will play a pivotal role in molding a manufacturing landscape that is both efficient and environmentally beneficial. However, achieving this potential will necessitate managing the dangers and difficulties that come with it carefully.

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

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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.

AI-POWERED HEALTHCARE REVOLUTION: AN EXTENSIVE EXAMINATION OF INNOVATIVE METHODS IN CANCER TREATMENT Murad Khan; Ashish Shiwlani; Muhammad Umer Qayyum; Abdul Mannan Khan Sherani; Hafiz Khawar Hussain
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 1 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract: This study examines the various ways that artificial intelligence (AI) is being used into the field of cancer medicine, with an emphasis on innovative techniques and advances in healthcare. The article, titled "AI Healthcare and Novel Approaches in the Field of Cancer Medicine," explores how AI is revolutionizing a number of fields, including population health management, clinical decision support, drug discovery, pathology analysis, diagnostic imaging, predictive modeling, and predictive modeling. The essay starts out by exploring the revolutionary role that artificial intelligence (AI) is playing in diagnostic imaging, where algorithms are demonstrating exceptional accuracy in identifying anomalies, especially in MRIs, CT scans, and mammograms. The tailoring of cancer treatments based on unique molecular profiles, bringing in a new age of targeted therapies, and minimizing side effects are the main themes that arise from precision oncology. AI-powered clinical decision support systems analyze a variety of patient data to improve the decision-making process for medical personnel. As a crucial component of cancer medicine, predictive modeling provides insights into disease development, therapeutic responses, survival prognostication, and the identification of high-risk patients. The study highlights how AI can improve clinical trials, speed up drug research and development, and change pathology and histology analysis to provide more precise cancer diagnosis.

Innovations in AI-Powered Healthcare: Transforming Cancer Treatment with Innovative Methods Saad Rasool; Mohammad Ali; Hafiz Muhammad Shahroz; Hafiz Khawar Hussain; Ahmad Yousaf Gill
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 1 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract: In this thorough review, we explore the multifaceted role of artificial intelligence (AI) in cancer medicine, highlighting its potential applications, challenges, and future directions. Artificial intelligence (AI) holds enormous promise for revolutionizing patient care and improving outcomes when integrated into various aspects of cancer medicine, including drug discovery and development, early detection and screening, and drug discovery. AI-driven methods in early detection and screening can increase sensitivity, decrease false-positive rates, and provide personalized risk assessment, which can boost the efficacy and efficiency of cancer screening programs. However, issues like algorithm bias, data quality, and regulatory compliance need to be resolved before AI can be fully utilized in this field. In addition, AI-driven drug discovery and development offers chances to speed up target identification, repurpose current medications, and create new therapeutics with improved safety and efficacy profiles. However, even with AI's potential to speed up drug discovery, issues with data accessibility, algorithm interpretability, and ethical implications still exist. Researchers, clinicians, regulators, and industry stakeholders must work together to develop strong data-sharing initiatives, ethical guidelines, and governance frameworks in order to address these challenges. By putting patient-centered approaches first, integrating multi-modal data, and encouraging interdisciplinary collaboration, we can harness the transformative power of AI to speed up the translation of research findings into novel therapies and enhance global cancer patient outcomes.

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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