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All Journal Journal of Computer Networks, Architecture and High Performance Computing Journal Of World Science Journal Research of Social Science, Economics, and Management
Yousaf Gill, Ahmad
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Computer Science & IT Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Social Sciences

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Role of Artificial Intelligence in Cardiovascular Health Care Khawar Hussain, Hafiz; Tariq, Aftab; Yousaf Gill, Ahmad
Journal of World Science Vol. 2 No. 4 (2023): Journal of World Science
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jws.v2i4.284

Abstract

In the field of cardiovascular health, machine learning and artificial intelligence (AI) have become effective tools with potential applications ranging from disease detection and diagnosis to individualized treatment planning and decision making. The purpose of this study is to identify and analyze the role of AI in cardiovascular health care. The methodology of this review paper involved an extensive literature review of the existing research on the topic of AI in cardiovascular health care. Medical imaging is very important in the diagnosis and treatment of many diseases, but the interpretation of medical images is often time-consuming and subjective. Artificial intelligence (AI) algorithms, such as supervised and unsupervised learning, have been developed to assist in the analysis and interpretation of data from medical imaging. Convolutional neural networks (CNNs) and support vector machines (SVM) are the two most frequently used AI algorithms in medical image analysis. Artificial intelligence (AI) and machine learning in cardiovascular healthcare have great potential to improve patient outcomes and lower costs. However, there are still some hurdles that need to be overcome such as integration with clinical workflows, model validation and generalization, and privacy and security issues related to patient data. To overcome this, collaboration between doctors, researchers and industrial partners is needed. This technology has a bright and promising future with continuous investment in research and development.
AI'S Healing Touch: Examining Machine Learning's Transformative Effects On Healthcare Husnain, Ali; Rasool, Saad; Saeed, Ayesha; Yousaf Gill, Ahmad; Khawar Hussain, Hafiz
Journal of World Science Vol. 2 No. 10 (2023): Journal of World Science
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jws.v2i10.448

Abstract

In the realm of healthcare, artificial intelligence (AI) emerges as a transformative force, reshaping established practices and offering unprecedented advancements. This comprehensive analysis delves into the multifaceted ways AI is revolutionizing healthcare, focusing on its transformative capabilities, inherent challenges, and the crucial ethical complexities entwined in its application. The challenge lies in balancing transparency and accountability amid the intricate algorithms, particularly concerning the interpretability of AI-generated insights. The analysis explores ethical dilemmas tied to patient autonomy and the evolving responsibilities of healthcare providers. It advocates for open dialogue among AI systems, patients, and healthcare professionals, navigating the delicate balance between innovation and patient welfare. The article emphasizes the imperative for robust ethical frameworks and regulations governing AI implementation in healthcare. The comprehensive investigation concludes by exploring AI's potential applications in healthcare, envisioning improved medical procedures, drug discoveries, remote patient monitoring, and diagnostic enhancements. To harness AI's transformative power while safeguarding patient interests, collaboration between healthcare professionals, data scientists, policymakers, and ethicists is paramount. This abstract encapsulates the profound shifts AI has initiated in healthcare, underscoring the vital need to harness its potential while addressing the ethical and regulatory complexities arising with its integration. Ultimately, it portrays a holistic view of AI's evolving role in healthcare, highlighting its potential to revolutionize patient care, medical practices, and the entire healthcare landscape.
Revolutionizing Healthcare: How Machine Learning is Transforming Patient Diagnoses - a Comprehensive Review of AI's Impact on Medical Diagnosis Yousaf Gill, Ahmad; Saeed, Ayesha; Rasool, Saad; Husnain, Ali; Khawar Hussain, Hafiz
Journal of World Science Vol. 2 No. 10 (2023): Journal of World Science
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jws.v2i10.449

Abstract

The integration of machine learning into healthcare heralds a new era where the convergence of technology and human compassion reshapes the very essence of healing. This monumental shift transcends mere technological advancement; it represents a profound evolution in patient care. By unraveling intricate patterns within medical data, machine learning empowers healthcare professionals with early disease detection and precise risk assessment, augmenting human intuition rather than replacing it. This synergy between AI-driven insights and human expertise has led to remarkable achievements, from redefining radiological interpretations to foreseeing infectious disease outbreaks, painting a future where healthcare is not only precise but profoundly patient-centered. Yet, amidst these groundbreaking advancements, ethical considerations stand as pillars guiding responsible innovation. Upholding patient autonomy, ensuring data privacy, and addressing algorithmic bias are essential to maintain trust and integrity. As we navigate this transformative path, the promise of a healthcare landscape where healing becomes a symphony of technology and tradition becomes evident. It is a future where the well-being and hopes of millions are at the core, promising a brighter, more compassionate tomorrow for healthcare, where every diagnosis, treatment, and act of care resonates with the harmony of human expertise and technological marvels.
Revolutionizing Healthcare: How Deep Learning is poised to Change the Landscape of Medical Diagnosis and Treatment Ahmad, Ahsan; Tariq , Aftab; Hussain , Hafiz Khawar; Yousaf Gill, Ahmad
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 2 (2023): Article Research Volume 5 Issue 2, July 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i2.2350

Abstract

Deep learning has become a significant tool in the healthcare industry with the potential to change the way care is provided and enhance patient outcomes. With a focus on personalised medicine, ethical issues and problems, future directions and opportunities, real-world case studies, and data privacy and security, this review article investigates the existing and potential applications of deep learning in healthcare. Deep learning in personalised medicine holds enormous promise for improving patient care by enabling more precise diagnoses and individualised treatment approaches. But it's important to take into account ethical issues like data privacy and the possibility of bias in algorithms. Deep learning in healthcare will likely be used more in the future to manage population health, prevent disease, and improve access to care for underprivileged groups of people. Case studies give specific examples of how deep learning is already changing the healthcare industry, from discovering rare diseases to forecasting patient outcomes. To fully realize the potential of deep learning in healthcare, however, issues including data quality, interpretability, and legal barriers must be resolved. Remote monitoring and telemedicine are two promising areas where deep learning is lowering healthcare expenses and enhancing access to care. Deep learning algorithms can be used to analyse patient data in real-time, warning medical professionals of possible problems before they worsen and allowing for online discussions with experts. Finally, when applying deep learning to healthcare, the importance of data security and privacy cannot be understated. To preserve patient data and guarantee its responsible usage, the appropriate safeguards and rules must be implemented. Deep learning has the ability to transform the healthcare industry by delivering more individualised, practical, and efficient care. However, in order to fully realize its promise, ethical issues, difficulties, and regulatory barriers must be solved. Deep learning has the potential to significantly contribute to enhancing patient outcomes and lowering healthcare costs with the right safeguards and ongoing innovation
Healthcare Revolution: How AI and Machine Learning Are Changing Medicine Saeed, Ayesha; Husnain, Ali; Rasool, Saad; Yousaf Gill, Ahmad; Amelia, Amelia
Journal Research of Social Science, Economics, and Management Vol. 3 No. 3 (2023): Journal Research of Social Science, Economics, and Management
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jrssem.v3i3.558

Abstract

This essay examines the enormous effects of machine learning and artificial intelligence (AI) on healthcare. Through data analysis, AI is transforming disease detection and prediction and improving the precision of diagnoses. By accelerating medication discovery and improving individualized treatment programs, it is revolutionizing both treatment and drug development. AI is promoting customized medicine by using genetic information to customize therapies. Through automation and optimized resource allocation, it is streamlining hospital processes. The importance of ethical considerations is significant; they center on data privacy, bias reduction, and accountability. The study highlights potential avenues for AI development, such as AI-driven drug discovery, predictive and preventative healthcare, advances in genomic medicine, enhanced medical imaging, and more robotics and automation. Predictive analytics, telehealth, AI virtual assistants, and AI in mental healthcare are all expected to grow. These developments have the potential to improve health care, streamline processes, and boost scientific inquiry. To use AI in healthcare in a fair and ethical manner, however, and usher in a future that is more patient-centric, accurate, and accessible internationally, difficulties related to data quality, ethics, regulation, and prejudice must be addressed.
Co-Authors Ahmad, Ahsan Amelia Amelia Husnain, Ali Hussain , Hafiz Khawar Khawar Hussain, Hafiz Rasool, Saad Saeed, Ayesha Tariq , Aftab Tariq, Aftab