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All Journal International Journal of Multidisciplinary Sciences and Arts BULLET : Jurnal Multidisiplin Ilmu Journal of ICT, Design, Engineering and Technological Science
Murad Khan
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Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Medicine & Pharmacology Nursing

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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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Abstract

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.
Utilizing Superpave Gradations to Assess Permanent Deformation and Fracture in HMA Mixes Muhammad Haris Javed; Inam Ur Rehman; Murad Khan; Akhtar Abbas; Adnan Khan
Journal of ICT, Design, Engineering and Technological Science Volume 6, Issue 1
Publisher : Journal of ICT, Design, Engineering and Technological Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33150/JITDETS-6.1.2

Abstract

This research study investigates the Fatigue Failure & Permanent Deformation response behaviour of four (04) HMA mixtures. The selected gradations have a Nominal Maximum Aggregate Size (NMAS) of 19.0 mm, and the gradation blends passed Above (ARZ), Below (BRZ), and Through (TRZ), the restricted zone. Along with the Superpave ARZ, BRZ & TRZ conventional NHA, “Class A” gradation was also checked for performance parameters, thus producing results in contrast to the conventional NHA gradation already used by highway industries Pakistan. Three (03) performance tests were carried out in this study that, includes Indirect Tensile Strength Test (IDT), the repeated Indirect Tensile Fatigue Test (ITFT), and the Moisture Susceptibility Test. Statistical analysis was also done based on laboratory-produced results. Two-Level Factorial Design was also carried out using the statistical tool Minitab-16. Statistical analysis shows that OBC, P0.075/Pbe (Dust to Binder Ratio), and the Peak Force significantly affect No of Cycles to Fatigue Failure. A linear Model was developed with an R square of .74 which seems to fit well. IDT Test evaluated the TRZ mix as having the best laboratory fracture resistance properties of all tested mixes, while ARZ performed best in the Moisture Susceptibility test. Moreover, this study gave us insight into Superpave IDT as a practical and reliable way to measure all the parameters needed in the HMA Fracture Mechanics method.
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.
Investigating the Strength Against Fire and Microstructure of Ultra-High-Performance Concrete Muhammad Haseeb Zaheer; Murad Khan; Adnan Khan; Hamayun Khan Kakar; Zohaib Ullah
Journal of ICT, Design, Engineering and Technological Science Volume 6, Issue 2
Publisher : Journal of ICT, Design, Engineering and Technological Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33150/JITDETS-6.2.4

Abstract

This study aims to produce Ultra-High-Performance Concrete utilizing locally available material. The experimental study includes silica fume with rice husk ash in combination with steel fibers. Various trials were made using different volumes of local materials and steel fibers to produce UHPC. Different properties were evaluated, such as compressive strength, tensile strength, and Scanning Electron Microscopy (SEM). Results show that UHPC can be produced using locally available materials as both the properties were examined with and without heating at higher temperatures and providing satisfactory strength. SEM tests were also performed to evaluate the microstructural study of the ultrahigh-performance concrete. SEM observations discovered that the transition zone between fine aggregates and the cement paste is improved by using silica.
Experimental Study on the Effects of Freeze-Thaw Progressions and Performance of Soil with Non-Toxic Bio-Enzyme Garzali Gali; Adnan Khan; Salman khan; Shahzad khalil; Qaim Shah; Murad Khan
Journal of ICT, Design, Engineering and Technological Science Volume 7, Issue 1
Publisher : Journal of ICT, Design, Engineering and Technological Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33150/JITDETS-7.1.3

Abstract

The Yakhtangay (Cold Valley) in District Shangla is encountering severe freeze-thaw cycles due to its elevated location and cold weather conditions. Repeated cycles of freeze-thaw action on soil cause it to lose strength, leading to settlement and a decrease in compressive strength. The objective of the study is to investigate the potential of terrazyme in enhancing the compressive strength of soil subjected to freeze and thawing cycles. Terrazyme, a bio enzyme obtained from plants and soluble in water, can reduce the water content from the soil while increasing inter-particle cohesion, leading to improved soil strength. The laboratory tests were conducted on both treated and untreated soil samples, and their properties were compared. The experimental study also included performing tests such as grain size distribution, Atterberg's limits, compaction, and compressive strength on the soil samples. Unconfined Compression Samples (UCS) were prepared and tested for freeze and thaw cycles in treated and untreated forms. The research utilized the optimal amount of Terrazyme, reducing water moisture content from 13% to 11%. Furthermore, using Terrazyme significantly increased soil compressive strength, with an improvement of 40%. Based on the study's results, terrazyme is proposed as a highly effective soil admixture that can significantly enhance soil properties—particularly its resistance against the negative impact of freeze-thaw cycles. This study can be implicated practically to avoid freeze-thaw problems in the soil of cold regions and can be proved fruitful for the researchers to study on the particular and related topics.
To Stabilize Shear Strength Properties of an Unwanted Subgrade Soil Utilizing Rock Dust Qaim Shah; Kwabene Byemba; Garzali Gali; Ali Muhammad; Adnan Khan; Murad Khan
Journal of ICT, Design, Engineering and Technological Science Volume 7, Issue 2
Publisher : Journal of ICT, Design, Engineering and Technological Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33150/JITDETS-7.2.1

Abstract

When a pavement fails, the subgrade is displaced laterally due to the pavement absorbing water, excessive deflection, and differential settling of the material beneath the pavement. The purpose of the study is to determine how rock dust additions affect the stability and increased bearing capacity of certain soils in Mardan City. For the objective of stabilizing the native soil, the physical, chemical, and engineering qualities of the soil were investigated. The soils were then treated with additions (rock dust). Rock dust is added to soils with a percentage increase of 5%, 10%, and 15%, respectively, to stabilize soils from 0 to 85%. Atterberg limits (liquid limit, plasticity index, and plastic limit), Specific Gravity, gradations test, and direct shear test were performed on the treated sample. The exact temperature and moisture content for maturation were applied to all samples. The results of the particle size study indicated that the soil's gradation is thin. With the addition of rock dust, the plasticity index (P.I.), liquid limit (L.L.), and plastic limit (P.L.) were all reduced. With the addition of rock dust, it was discovered that the value of cohesion c reduced, and the angle of internal friction decreased. The Research revealed that rock dust, at an ideal concentration of 10%, is the best stabilizer for the case study (Toru Road, Mardan City).
Water Pollution Hazards and Toxicity Caused by Textile Industries Effluent Ghulam Mujtaba; Noor Muhammad; Qaim Shah; Murad Khan; Nabeel K. Abbood
Journal of ICT, Design, Engineering and Technological Science Volume 7, Issue 2
Publisher : Journal of ICT, Design, Engineering and Technological Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33150/JITDETS-7.2.3

Abstract

Water pollution is a serious environmental problem that endangers both human health and ecosystems. Due to its heavy use of chemicals and water-intensive processes, the textile industry is one of the biggest contributors to water pollution. Water contamination occurs when effluent from textile manufacturing facilities enters water bodies including rivers, lakes, and groundwater after being improperly or not at all treated. These contaminants may have negative impacts on aquatic life, including reducing their capacity for reproduction, upsetting ecosystems, and even killing aquatic organisms. Furthermore, anyone who uses contaminated water sources for agriculture, pleasure, or drinking can face major health hazards. Heavy metals, volatile organic compounds (VOCs), surfactants, and other harmful substances are some of the pollutants identified in effluent from the textile industry. To reduce water pollution, this abstract emphasizes the critical necessity for sustainable practices in the textile industry for which different investigatory experimental performances were done to highlight and resolve the issue. Chloride content, turbidity and hardness tests were done to evaluate the hazards that are caused by the water pollution. It is possible to lessen the environmental impact of textile production and protect water resources for future generations by implementing efficient pollution prevention measures and adopting cleaner production techniques.
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.
Co-Authors Abdul Mannan Khan Sherani Adnan Khan Akhtar Abbas ALI MUHAMMAD Ashish Shiwlani Garzali Gali Ghulam Mujtaba Hafiz Khawar Hussain Hamayun Khan Kakar Inam Ur Rehman Kwabene Byemba Muhammad Haris Javed Muhammad Haseeb Zaheer Muhammad Umer Qayyum Nabeel K. Abbood Noor Muhammad Qaim Shah Salman Khan Shahzad Khalil Zohaib Ullah