ALI HUSNAIN

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Andrej Dujella

University of Zagreb

Hemin Koyi

Uppsala University

Jana Javornik

University of East London

Graham Martin

University of Leicester

Gwen Robbins Schug

University of North Carolina at Greensboro

Gabriel Gutierrez-Alonso

University of Salamanca

John Sutton

Macquarie University

Eros Carvalho

Universidade Federal do Rio Grande do Sul

Kevin Arbuckle

Swansea University

Jesper Hoffmeyer

University of Copenhagen

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Papers by ALI HUSNAIN

AI'S Healing Touch: Examining Machine Learning's Transformative Effects On Healthcare

Journal Of World Science, Oct 29, 2023

In the realm of healthcare, artificial intelligence (AI) emerges as a transformative force, resha... more 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.

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Dynamic Modeling of a Micro Solar Electric Vehicle for Pakistan using Simulink

2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)

While the global electric vehicle (EV) adoption is on rise, developing countries like Pakistan ha... more While the global electric vehicle (EV) adoption is on rise, developing countries like Pakistan have been facing many obstacles in the face of EV adoption such as shortfall of electricity, high EV prices, low average income and absence of commercial and residential charging infrastructure. In this paper, we propose a design of a micro solar electric vehicle, which would help overcome all of these problems and provide an economical yet feasible solution. The design and system sizing of the micro solar EV was done in HOMER Pro. A dynamic model of the micro solar EV was created in MATLAB/Simulink, which implemented PV generation, maximum power point tracking, battery charging and discharging, DC-motor operation and speed control of the electric vehicle, while taking into consideration environmental factors like irradiance and temperature.

System Design and PV Sizing of a Micro Solar Electric Vehicle for Pakistan

2022 IEEE Conference on Technologies for Sustainability (SusTech)

Transport sector is the third largest contributor of GHG emissions globally. To counter this, glo... more Transport sector is the third largest contributor of GHG emissions globally. To counter this, global EV adoption has been increasing at a rapid rate. However, Pakistan has been left far behind in this race and is very slow to EV adoption, due to a number of factors including energy shortfall, lack of purchase power and absence of charging infrastructure to name a few. Therefore, a design for simple yet economical micro solar electric vehicle has been proposed. This paper covers the sizing and system design for the solar PV system for a solar electric vehicle on HOMER Pro. It also gives an economic analysis of all the components involved.

Estimating market trends by clustering social media reviews

2017 13th International Conference on Emerging Technologies (ICET), 2017

In recent years, social media networks have expanded in size and utility. Sites like Facebook and... more In recent years, social media networks have expanded in size and utility. Sites like Facebook and Twitter have become giant pools of available public information. Across the globe, millions of users exchange information and sentiments daily. Realizing the importance of cyber reach, all major companies and brands have ensured their presence on all social media platforms. Companies like YouTube, Google, P&G, McDonald's continuously update their consumers pertaining to changes in their products. In this paper we have drawn an interesting relationship between the brand updates and the response garnered by them. Using the response to those updates, we have developed a causal link between the producers and consumers. We have clustered the response data on geographic parameters to see the distribution of users. To add more perspective to the information gathered, we have used sentiment analysis to distinguish positively or negatively distributed clustered data. Such a distribution gives an overview of consumer market diversity and can help the producers make better estimates of user reviews. The major contribution of this paper is introducing novel use-case of social media platforms to determine the market trends that can help investors in analyzing their performance.

Revolutionizing Pharmaceutical Research: Harnessing Machine Learning for a Paradigm Shift in Drug Discovery

International Journal of Multidisciplinary Sciences and Arts, Sep 27, 2023

The fusion of machine learning (ML) and artificial intelligence (AI) is experiencing a dramatic t... more 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.

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AI'S Healing Touch: Examining Machine Learning's Transformative Effects On Healthcare

Journal Of World Science, Oct 29, 2023

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Dynamic Modeling of a Micro Solar Electric Vehicle for Pakistan using Simulink

2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)

System Design and PV Sizing of a Micro Solar Electric Vehicle for Pakistan

2022 IEEE Conference on Technologies for Sustainability (SusTech)

Estimating market trends by clustering social media reviews

2017 13th International Conference on Emerging Technologies (ICET), 2017

Revolutionizing Pharmaceutical Research: Harnessing Machine Learning for a Paradigm Shift in Drug Discovery

International Journal of Multidisciplinary Sciences and Arts, Sep 27, 2023

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