The legal and ethical issues that confront society due to Artificial Intelligence (AI) include privacy and surveillance, bias or discrimination, and potentially the philosophical challenge is the role of human judgment. Concerns about newer digital technologies becoming a new source of inaccuracy and data breaches have arisen as a result of its use. Mistakes in the procedure or protocol in the field of healthcare can have devastating consequences for the patient who is the victim of the error. Because patients come into contact with physicians at moments in their lives when they are most vulnerable, it is crucial to remember this. Currently, there are no well-defined regulations in place to address the legal and ethical issues that may arise due to the use of artificial intelligence in healthcare settings. This review attempts to address these pertinent issues highlighting the need for algorithmic transparency, privacy, and protection of all the beneficiaries involved and cybersecurity of associated vulnerabilities.

Data science is an interdisciplinary field that extracts knowledge and insights from many structural and unstructured data, using scientific methods, data mining techniques, machine-learning algorithms, and big data. The healthcare industry generates large datasets of useful information on patient demography, treatment plans, results of medical examinations, insurance, etc. The data collected from the Internet of Things (IoT) devices attract the attention of data scientists. Data science provides aid to process, manage, analyze, and assimilate the large quantities of fragmented, structured, and unstructured data created by healthcare systems. This data requires effective management and analysis to acquire factual results. The process of data cleansing, data mining, data preparation, and data analysis used in healthcare applications is reviewed and discussed in the article. The article provides an insight into the status and prospects of big data analytics in healthcare, highlights the advantages, describes the frameworks and techniques used, briefs about the challenges faced currently, and discusses viable solutions. Data science and big data analytics can provide practical insights and aid in the decision-making of strategic decisions concerning the health system. It helps build a comprehensive view of patients, consumers, and clinicians. Data-driven decision-making opens up new possibilities to boost healthcare quality.

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Background The Coronavirus disease (COVID-19) outbreak in 2019, has shocked the entire world. As an effort to control the disease spread, the Indian government declared a nationwide lockdown on March 25th, 2020. As dental treatment was considered high risk in the spread of COVID-19, dentistry became one of the most vulnerable professions during this time. Dental professionals had to face job layoffs, salary cuts in professional colleges, closure of private clinics resulting in huge psychological, moral, and financial crises. Studies during the previous and present pandemics have shown mental issues among health care workers necessitating institutional reforms, along with early care and support. A balance in the work-life amongst professionals is the key to better efficiency and, was majorly affected during the COVID-19 pandemic lockdown due to sudden unexpected changes. Hence this study was conducted to understand the changes they underwent both at home and professional front with a hypothesis that physical and mental health, activities, relationship status, and workplace influence the work-life balance. Methods A pre-validated questionnaire survey was done on dentists across India. Structural Equation Modelling and path analysis were applied to the data collected. Results The results of the study supported the hypothesis that factors like physical and mental health, activities, relationship status, and workplace influenced the work-life balance directly. A significant imbalance was seen amongst the female dentists. Conclusion The present study proved the unpreparedness among dental professionals. Hence an evolutionary phase in every field with better working protocols, robust mental health support, and a focus on strategies to face future such emergencies is required.