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All Journal International Journal of Multidisciplinary Sciences and Arts BULLET : Jurnal Multidisiplin Ilmu
Hafiz Khawar Hussain
Unknown Affiliation
Humanities Computer Science & IT Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing

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Revolutionizing Pharmaceutical Research: Harnessing Machine Learning for a Paradigm Shift in Drug Discovery Ali Husnain; Saad Rasool; Ayesha Saeed; Hafiz Khawar Hussain
International Journal of Multidisciplinary Sciences and Arts Vol. 2 No. 4 (2023): 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.v2i2.2897

Abstract

The fusion of machine learning (ML) and artificial intelligence (AI) is experiencing a dramatic transition in the field of pharmaceutical research and development. This study examines the several effects of machine learning (ML) on different phases of medication discovery, development, and patient care. The capability of ML to quickly process huge chemical libraries and forecast interactions with target proteins is studied, starting with compound screening and selection. The potential for fewer false positives and negatives, improved hit prediction accuracy, and ensemble technique use are underlined. The part that machine learning plays in enhancing Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) profile is then explained. ML models anticipate compound actions inside the human body by analyzing molecular structures and characteristics, improving assessments of drug safety and efficacy. The article goes into further detail about predictive modeling, highlighting how machine learning may be used to find prospective therapeutic targets and confirm their applicability. The combination of multi-omics data, deep learning, and the possibility to identify similar molecular pathways across diseases highlight the game-changing potential of machine learning in this field. The article also covers the use of ML in clinical trials, highlighting its benefits for trial planning, patient recruitment, real-time monitoring, and individualized therapy predictions. By utilizing computational analysis and quantum physics, the power of machine learning-driven de novo drug creation is examined, revealing the potential to develop new therapeutic candidates. In this article, the ethical issues surrounding AI-driven drug discovery are discussed, with a focus on the necessity of transparent data utilization, human oversight, and responsible data consumption. The report ends by predicting ML's potential for pharmaceutical R&D in the future. Accelerated drug discovery pipelines, the rise of customized medicine powered by predictive models, optimized clinical trials, and a change in medication repurposing tactics are all envisaged in this. The report emphasizes the revolutionary potential of ML in altering pharmaceutical research and development while noting obstacles in data quality, model interpretability, ethics, and interdisciplinary collaboration. It is suggested that the ethical integration of AI technologies, interdisciplinary cooperation, and regulatory modifications are essential steps to unlock the full potential of ML and AI and, ultimately, provide patients throughout the world with safer, more efficient, and individualized treatments.
Future Horizons: AI-Enhanced Threat Detection in Cloud Environments: Unveiling Opportunities for Research Haroon Arif; Aashesh Kumar; Muhammad Fahad; Hafiz Khawar Hussain
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 1 (2024): International Journal of Multidisciplinary Sciences and Arts, Article January 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v2i2.3452

Abstract

In this extensive and comprehensive review paper, we delve into the dynamic landscape of artificial intelligence (AI)-enhanced threat detection within cloud environments. The evolution of this field, from traditional methodologies to the seamless integration of AI, is meticulously explored, providing a nuanced understanding of the transformative potential of AI in bolstering cyber security measures. The exploration encompasses a myriad of crucial aspects, offering readers a holistic view of the subject. The revolutionary impact of AI is scrutinized, emphasizing its role in reshaping the conventional paradigms of threat detection and response. The paper meticulously addresses current challenges in cloud security, providing insights into the multifaceted nature of contemporary threats and how AI serves as a robust defense mechanism. As we navigate through the intricacies of this field, the review paper sheds light on ongoing research prospects, presenting a roadmap for future endeavors. Real-world case studies are examined to illustrate the practical applications of AI-enhanced threat detection, offering valuable lessons and perspectives for decision-makers, researchers, and practitioners in the realm of cyber security. Ethical considerations are given due attention, as the integration of AI in threat detection raises important questions surrounding privacy, bias, and accountability. By analyzing current trajectories and emerging technologies, the article provides readers with a forward-looking perspective, helping them anticipate the evolving landscape of cyber security. In addition to exploring the technological facets, the paper emphasizes the importance of a collaborative approach and ongoing adaptation. The interconnected nature of threats in the digital realm necessitates a collective effort from industry experts, researchers, and policymakers. The review paper advocates for a holistic strategy that integrates AI technologies with human expertise to create a resilient defense against the ever-evolving landscape of cyber threats.
Synergizing AI and Healthcare: Pioneering Advances in Cancer Medicine for Personalized Treatment Abdul Mannan Khan Sherani; Murad Khan; Muhammad Umer Qayyum; Hafiz Khawar Hussain
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 2 (2024): International Journal of Multidisciplinary Sciences and Arts, Article April 202
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i01.3562

Abstract

This paper investigates how Artificial Intelligence (AI) is changing the field of cancer medicine. It is organized into nine major sections that illustrate the profound effects of AI on different aspects of cancer care. Starting from the early phases of the disease, AI shows how it can transform conventional diagnostic methods by providing quick and accurate analyses of medical imaging, pathology slides, and genetic data. The paper then goes into the era of personalized cancer therapies, highlighting the ways in which AI helps to customize treatment based on individual genetic and molecular profiles. Finally, the paper discusses the smart revolution in healthcare, which is driven by AI integration, highlighting the impact of AI on diagnosis precision, treatment optimization, and resource allocation. Moreover, the story delves into how AI is being incorporated into healthcare outside of diagnosis and treatment, including areas like predictive modeling, ongoing monitoring, and after-treatment care. AI has the capacity to revolutionize cancer medicine by improving current practices and fostering innovation in clinical research, diagnosis modalities, and treatment planning. The paper highlights the revolutionary boundaries that AI has created, including liquid biopsies, virtual tumor boards, and the speeding up of drug discovery processes. The narrative weaves a thorough overview of AI's transformative journey in cancer care, offering insights into its current impact and the promising possibilities that lie ahead.
Revolutionizing Healthcare with AI: Innovative Strategies in Cancer Medicine Murad Khan; Ashish Shiwlani; Muhammad Umer Qayyum; Abdul Mannan Khan Sherani; Hafiz Khawar Hussain
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 2 (2024): International Journal of Multidisciplinary Sciences and Arts, Article April 202
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i1.3922

Abstract

By improving early detection, diagnosis, treatment planning, and patient management, artificial intelligence (AI) is transforming the way that cancer is treated. An overview of AI's function in cancer is given in this article, with special attention to how it advances precision medicine and improves patient outcomes. Numerous AI applications are discussed, such as predictive analytics, pathology interpretation, genetic profiling, and medical imaging analysis. Case studies highlight effective AI applications in cancer care, showcasing the technology's effectiveness in enhancing the precision of diagnoses, directing individualized treatment choices, and tracking treatment response. The paper delves into the possible advancements in early identification, therapy optimization, and patient engagement through an exploration of future directions and innovations in AI-driven oncology research. The conclusion emphasizes how AI has the ability to completely change the way cancer is treated and enhance the lives of cancer sufferers all over the world.
Equity and Artificial Intelligence in Surgical Care: A Comprehensive Review of Current Challenges and Promising Solutions Ahsan Ahmad; Aftab Tariq; Hafiz Khawar Hussain; Ahmad Yousaf Gill
BULLET : Jurnal Multidisiplin Ilmu Vol. 2 No. 2 (2023): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

The use of artificial intelligence (AI) has become a viable method for improving surgical care equity. In order to better understand the effects of AI in surgical settings, this paper focuses on five key areas: promising AI applications, bias-reduction tactics, and ethical AI implementation, effects on patient outcomes and access to surgical services, and future directions for equitable AI in surgical care. The first part of the article looks at the exciting uses of AI in surgery. It emphasizes how AI technology may boost decision-making, increase surgical precision, and improve patient care routes. Better surgical outcomes, individualised treatment plans, and streamlined procedures can all result from the incorporation of AI algorithms, which will ultimately help patients from a variety of groups. The solutions for reducing bias and fostering equity in AI-enabled surgical care are covered in more detail in the second part. In order to reduce biases, it emphasizes the value of diverse and representative datasets, algorithmic transparency, and fairness metrics. Healthcare disparities can be decreased by proactively addressing bias, and AI-enabled surgical care can help ensure fair outcomes for all patient populations. The final segment is devoted to removing obstacles in the way of deploying moral AI procedures in surgical settings. It places a strong emphasis on the necessity of open governance structures, informed consent procedures, privacy protection, accountability, and ongoing ethical assessment. Accountability is guaranteed through transparent governance systems, which also offer a way to address moral issues and potential biases. The implications of AI for patient outcomes and access to surgical services are covered in the fourth part. It emphasizes how AI technologies have the potential to enhance decision-making, improve surgical results, and streamline patient care routes. It also covers issues with bias, privacy, and ethics that must be taken into account to enable responsible and fair implementation. The fifth segment examines potential future directions and surgical care opportunities for egalitarian AI. Strong data infrastructure, advances in deep learning and machine learning, explainable AI, AI-driven surgical automation, tackling health disparities, and the creation of ethical and legal frameworks are some of the themes it highlights. These regions have enormous opportunity to improve patient outcomes and advance fair access to surgical care. Enhancing equity is made possible by the incorporation of AI in surgical care. Healthcare organizations can enhance surgical results, lower inequities, and guarantee equitable access to surgical services by utilizing AI technologies. To be responsible and equitable, a deployment must address bias, adhere to ethical standards, and take into account how AI is developing. To maximize the advantages of AI in surgical care while advancing equity and patient-centered care, future research and collaboration are crucial.
Navigating the Uncharted Waters: Exploring Challenges and Opportunities in Block chain-Enabled Cloud Computing for Future Research Aashesh Kumar; Muhammad Fahad; Haroon Arif; Hafiz Khawar Hussain
BULLET : Jurnal Multidisiplin Ilmu Vol. 2 No. 6 (2023): BULLET : Jurnal Multidisiplin Ilmu (INPRESS)
Publisher : CV. Multi Kreasi Media

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Abstract

This article offers a thorough examination of the prospects, challenges, and future directions of block chain-enabled cloud computing, navigating a field that is still relatively new. The study explores the intricacies of the integration, from laying forth fundamental ideas to analyzing the present situation. Case studies shed light on effective implementations in the fields of finance, healthcare, supply chains, and other areas, offering insightful guidance for future initiatives. Examined are the transformative potential, security consequences, and regulatory considerations, highlighting the importance of sound frameworks and responsible development. Important factors including cooperation, sustainability, privacy, user education, regulatory clarity, and ongoing research are outlined in the roadmap for the future. In summary, the paper predicts a revolutionary digital future where block chain technology and cloud computing combine to foster creativity, cooperation, and resilience.
Co-Authors Aashesh Kumar Abdul Mannan Khan Sherani Aftab Tariq Ahmad Yousaf Gill Ahsan Ahmad Ali Husnain Arbaz Haider Khan Ashish Shiwlani Ayesha Saeed Hafiz Muhammad Shahroz Haroon Arif Hira Zainab Mohammad Ali Muhammad Fahad Muhammad Umer Qayyum Murad Khan Roman Khan Saad Rasool Shahrukh Khan Lodhi