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The introduction of Chat Generative Pre-Trained Transformer (ChatGPT) in November 2022 brought about rapid changes in the workplace and academia. Its usage ranged from student assignments to workplace targets in the engineering field. Although it has brought novel ideas to its application in various fields and task efficiency in the workplace, its perceived application varies among students, teachers, and professionals. This study employed the snowball sampling technique and interviews with eight students, eight faculty members, and eight working professionals from computer science engineering who used ChatGPT regularly. The study adopted a qualitative research design and employed the narrative data analysis technique. Researchers conducted in-depth, semi-structured interviews to elicit user experiences from the recruited samples. The findings brought out six main and twelve subordinate themes regarding ChatGPT user experiences: adapt, adopt, embrace, ease, speed, engage, and automate. The inclusion criteria involved ChatGPT users from the computer science engineering domain only. Future research may focus on developing ChatGPT user policies for various fields of their applications. [ABSTRACT FROM AUTHOR]

On the Indian subcontinent, where a billion hearts beat, cancer casts a long shadow. In this crucible of healthcare innovation, the researchers shift their focus to India, a land as diverse as its challenges. This research delves deep into the potential of artificial intelligence (AI) to transform cancer care within India’s unique ecosystem. Journeying to Kharghar, Maharashtra, a microcosm of the nation’s hopes and realities, the researchers assess the community’s attitude towards embracing AI-driven solutions. But amidst the enthusiasm lies a sobering truth: the specter of high cancer care costs looms large across India’s healthcare landscape. This research serves as a call to action, urging targeted government interventions tailored to the Indian context. Envisioning a future where AI-powered cancer care is democratized, hope replaces despair for millions battling this formidable foe. [ABSTRACT FROM AUTHOR]

India has become the most populous country in the world with over more than 1.4 billion people. Major portion of this population is not having an adequate insurance coverage. Rate of insurance penetration of India is very low as compare to other countries. The Indian Insurance industry is regulated by IRDAI and the regulatory framework has traditionally being very strict, the requirements for insurance licensing and capital are very tough. These are also some of the reasons for having less number of insurers in Indian insurance industry but recently, IRDAI, the Indian regulator has changed a lot and has proposed so many measures to facilitate the entry of new insurers in India. The Indian Insurance regulator is promoting product innovation and competition in the Indian insurance industry. The regulator is also aiming to create a conducive environment for achieving a goal of insurance for all by 2047. It is possible that in the near future Indian insurance industry will see a good number of new insurance players like the ways other countries are having, some of the important factors like competition, regulatory compliance, fulfilment of capital requirements and building trust among policyholders will continue to play a very important role in shaping the entry and growth of new insurance players. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) and Machine Learning (ML) are increasingly utilized in share market services due to significant efficiencies and benefits for companies and investors across the globe. This has resulted in an alteration in the firm's business models and has a potential impact on the effectiveness of the share market and could harm investors. Indian share market is also witnessing the usage of this technology by market intermediaries. The present regulatory framework of Securities Exchange Board of India (SEBI) on share market intermediaries is not dealing with the Fintech/technology 2.0-based products and services offered in retail trading and investment advisor platforms in India. The research is primarily based on the normative method presenting a qualitative analysis of the usage of AI & ML in various business models by share market intermediaries. How various share market regulators are addressing and regulating this technology usage and their judicial exposition. The paper concludes that the Indian share market is no exception & SEBI require to look at this new transformation and address the challenges posed by it. SEBI needs to take a proactive step to promote, guide & regulate usages of AI & ML which is gradually seeking the attention of Indian share market intermediaries into their business models and get the maximum benefit out of these technologies. [ABSTRACT FROM AUTHOR]

In recent years, India's entrepreneurship scene has grown. From entrepreneur's perspective this study examines the effectiveness of entrepreneurship using standard decision-making processes and AI. The study used a sample of 50 responses all over India. Entrepreneurs were asked to complete structured questionnaires and personal interviews to assess their opinions on traditional vs artificial intelligence, as well as the relationship between the two and their impact on entrepreneurial decisions. The results revealed that men and women entrepreneurs perceive personality and compatibility tests differently. [ABSTRACT FROM AUTHOR]

With the emerging complexities in chronic diseases and people's lifestyles, healthcare professionals (HCPs) need to update their methods to manage and educate patients with chronic lifestyle disorders, particularly diabetes. The insulin injection technique (IIT), along with various parameters, must also be updated with newer methods. Forum for Injection Technique and Therapy Expert Recommendations (FITTER), India, has updated its recommendations to cover newer ways of detecting hypoglycaemia and lipohypertrophy, preventing needlestick injuries (NSIs), discouraging the reuse of insulin needles and encouraging good disposal. FITTER, India, is also introducing recommendations to calculate insulin bolus dose. These updated recommendations will help HCPs better manage patients with diabetes and achieve improved outcomes. [ABSTRACT FROM AUTHOR]

The government of India is the final authority for country-wide policy making and policy implementation in the country. Recent times have witnessed increasing use of data-driven approaches in policy and decision making. This is true for public policy formulation as well. This paper is an effort to highlight how data science and artificial intelligence have the potential to revolutionize the field of public policy in India. The paper discusses some such applications and lists down the likely challenges. An extensive review of the research activities in this field has been undertaken. Cases of data science and artificial intelligence reviewed in this paper span over various sectors of public policy such as- policy making process, health, education, environment, agriculture, economy, and security. This paper, thus, aims to facilitate collaboration in the fields of public policy and data technology, in order to enable higher levels of public service in India. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases (CVDs) in India and globally are the major cause of mortality, as revealed by the World Health Organization (WHO). The irregularities in the pace of heartbeats, called cardiac arrhythmias or heart arrhythmias, are one of the commonly diagnosed CVDs caused by ischemic heart disease, hypertension, alcohol intake, and stressful lifestyle. Other than the listed CVDs, the abnormality in the cardiac rhythm caused by the long term mental stress (stimulated by Autonomic Nervous System (ANS)) is a challenging issue for researchers. Early detection of cardiac arrhythmias through automatic electronic techniques is an important research field since the invention of electrocardiogram (ECG or EKG) and advanced machine learning algorithms. ECG (EKG) provides the record of variations in electrical activity associated with the cardiac cycle, used by cardiologists and researchers as a gold standard to study the heart function. The present work is aimed to provide an extensive survey of work done by researchers in the area of automated ECG analysis and classification of regular & irregular classes of heartbeats by conventional and modern artificial intelligence (AI) methods. The artificial intelligence (AI) based methods have emerged popularly during the last decade for the automatic and early diagnosis of clinical symptoms of arrhythmias. In this work, the literature is explored for the last two decades to review the performance of AI and other computer-based techniques to analyze the ECG signals for the prediction of cardiac (heart rhythm) disorders. The existing ECG feature extraction techniques and machine learning (ML) methods used for ECG signal analysis and classification are compared using the performance metrics like specificity, sensitivity, accuracy, positive predictivity value, etc. Some popular AI methods, which include, artificial neural networks (ANN), Fuzzy logic systems, and other machine learning algorithms (support vector machines (SVM), k-nearest neighbor (KNN), etc.) are considered in this review work for the applications of cardiac arrhythmia classification. The popular ECG databases available publicly to evaluate the classification accuracy of the classifier are also mentioned. The aim is to provide the reader, the prerequisites, the methods used in the last two decades, and the systematic approach, all at one place to further purse a research work in the area of cardiovascular abnormalities detection using the ECG signal. As a contribution to the current work, future challenges for real-time remote ECG acquisition and analysis using the emerging technologies like wireless body sensor network (WBSN) and the internet of things (IoT) are identified. [ABSTRACT FROM AUTHOR]

As a result of Covid-19 distresses the economy and its impact on agriculture. This is complex and farmers have faced many problems, such as the unavailability of labour due to the lockdown and relocation of farmers to their locations and access to the market is difficult because transportation facilities were not available during the lockdown period and it is very difficult for farmers to repay loans in this period. Indian Council for Agricultural Research (ICAR) has been proposing agricultural reforms using technical innovation and attempting to safeguard farmers from losses. The goal of the research is to through a light on the structure of Indian agriculture and to give policy suggestions. It had been observed that, transportation stopped because of the lockdown making the farm economy go nowhere. The produce was unable to be transported to market, thereby disturbing the supply chain in the middle of the harvest period. Also, the non-availability of migrant laborers, seizing the harvest and post-harvest operations. The pandemic has made to several contests in procurement operations as well as agricultural operations in future the following new techniques such as mechanical soil ploughing, automatic irrigation system, advanced weather monitoring, app-based system, online knowledge and market conditions, advanced technologies can be leveraged. In order to help the farmers to find more effective ways to defend their crops from weeds, the farmers can use automation and robotics. A Blue River Technology-developed robot named See & Spray appears to have been industrialized to use computer vision to precisely spray weeds on cotton plants. There are more advanced technologies using Artificial Intelligence (AI) and agricultural robotics to save water, sustain agro-ecology, rotate crops, and plant cover crops, alternating with manual labour that can keep farming activities going without hitch. [ABSTRACT FROM AUTHOR]

In many developing countries like India, there is a widespread lack of general awareness about the importance of good oral health, which causes dental patients to neglect their oral hygiene, thus precipitating many long-term ailments. We developed an application that promotes the significance of regular dental checkups and oral health care by explaining to patients how these are intrinsic to overall health. Our application, in essence, extracts relevant health information from published scientific studies according to a patient's medical history and shares it with the patient at the discretion of the supervising dentist, thereby empowering patients to make more informed decisions. We present a detailed overview of our semi- autonomous machine learning-based solution, along with the complex challenges involved in the design, development, and real-world deployment of our application. Finally, we conducted a randomized parallel-group study in India with 224 dental patients over two years to assess the utility of our proposed solution. Results show our application improved the patient recall rate from 21.1% to 37.8% (p-value = 0.024).