Short Keynote Paper: Mainstreaming Personalized Healthcare-Transforming Healthcare through new era of Artificial Intelligence

Paranjape, Ketan; Schinkel, Michiel; Nanayakkara, Prabath W.B.

doi:10.1109/jbhi.2020.2970807

Cited by 35 publications

(44 citation statements)

References 37 publications

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“…As the healthcare data is huge in volume an increase significantly, exploiting AI (e.g., deep learning) to develop data-driven healthcare solutions has become one important trend in healthcare research and development [158]. Meanwhile, since most patients do not want to share their personal health data, if not mandatorily requested by the governments and medical staffs, effectively overcoming the security and privacy challenges of healthcare data usage is of importance.…”

Section: J Personalized Body Area Networkmentioning

confidence: 99%

Survey on 6G Frontiers: Trends, Applications, Requirements, Technologies and Future Research

Alwis

Kalla

Pham

et al. 2021

IEEE Open J. Commun. Soc.

498

195

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Emerging applications such as Internet of Everything, Holographic Telepresence, collaborative robots, and space and deep-sea tourism are already highlighting the limitations of existing fifth-generation (5G) mobile networks. These limitations are in terms of data-rate, latency, reliability, availability, processing, connection density and global coverage, spanning over ground, underwater and space. The sixth-generation (6G) of mobile networks are expected to burgeon in the coming decade to address these limitations. The development of 6G vision, applications, technologies and standards has already become a popular research theme in academia and the industry. In this paper, we provide a comprehensive survey of the current developments towards 6G. We highlight the societal and technological trends that initiate the drive towards 6G. Emerging applications to realize the demands raised by 6G driving trends are discussed subsequently. We also elaborate the requirements that are necessary to realize the 6G applications. Then we present the key enabling technologies in detail. We also outline current research projects and activities including standardization efforts towards the development of 6G. Finally, we summarize lessons learned from state-of-the-art research and discuss technical challenges that would shed a new light on future research directions towards 6G.

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Section: J Personalized Body Area Networkmentioning

confidence: 99%

Survey on 6G Frontiers: Trends, Applications, Requirements, Technologies and Future Research

Alwis

Kalla

Pham

et al. 2021

IEEE Open J. Commun. Soc.

498

195

View full text Add to dashboard Cite

show abstract

“…In the present day, AI has unquestionably helped numerous doctors, medical care experts, and clinicians. Paranjape et al (2020) Besides every one of these examinations, there is also a conviction that it will require numerous years for AI to substitute people for broad clinical cycle areas.…”

Section: Data and Coordinated Medical Care Administrationsmentioning

confidence: 99%

Artificial Intelligence at Healthcare Industry

Gadde¹

2021

IJRASET

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I. INTRODUCTIONThroughout the long term, human insight has created numerous folds. Hamet P &Tremblay J. It had been the 1930s; the humanity had the virtual PC working practically the size of present-day rooms. The 1970s was the time we began utilizing small PCs inside the medical services area. From using the PCs for medical clinic charging, monetary applications, and doctor charging to using the PCs for finding and treatment suggestions, these days, PCs play a massive job in different areas of the medical care area. The entirety of this has been conceivable simply because of the improvement of Artificial Intelligence. Davenport (2019). Nowadays, AI has been a great assistance in determination, treatment suggestions, relentless commitment, and authoritative exercises to the expert medical care laborers. Studies recommend that AI be able to play out some errands, for example, diagnosing the sickness equivalent to or better than people. There are many territories where the conventional clinical medical care frameworks can't safeguard an individual from falling prey to death. A portion of the spaces can be ensured effectively with the assistance of Man-made reasoning. Rita (2019). Referencing a part of the difficulties looked by the area are: A. Installment Handling and InvoicingNumerous individuals don't have an issue in managing their treatment. However, they have problems with managing the cost of the after-treatment medication. There are requests for successful charging cycles and strategy models, where quality is resolved first, and afterward comes the amount. This requires vast scope usage of change in medical care installment preparing models. Presently this is the place where Artificial Intelligence can do the work productively and viably. With appropriate prepared informational indexes from clinical exercises, such as screening, conclusion, treatment task, and others, AI can be sent here for a human-like working or even an excellent working.

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“…There are many kinds of unsupervised matrix decomposition methods. 19,20) Among these, we have selected the factor analysis principal component method because the outcomes of its analysis are relatively easy to interpret, due to its linear property approach. Because most biological phenomena are considered to be non-linear processes, in general, it is difficult to grasp where the outcomes of machine learning would be derived, which thus reduces the chance to utilize existing bodies of biological knowledge and human wisdom.…”

Section: Decomposition Of Multiple Effects Of a Drug: Orthogonal Linementioning

confidence: 99%

Interesting Properties of Profile Data Analysis in the Understanding and Utilization of the Effects of Drugs

Mizuno

Morita

Kusuhara

2020

Biological & Pharmaceutical Bulletin

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Profile data is defined as data which describes the properties of an object. Omics data of a specimen is profile data because its comprehensiveness supports the idea that omics data is numeric information which reflects biological information of the specimen. In general, omics data analysis utilizes an existing body of biological knowledge, while some profile data analysis methods are independent of existing knowledge, which is suitable for uncovering unidentified aspects of a specimen of interest. The effects of a small compound, such as drugs, are multiple, and include unrecognized effects, even by the developers. To uncover such unrecognized effects, it is useful to employ profile data analysis independent of existing knowledge. In this review, we summarize what profile data is, properties of profile data analysis, and current applications of profile data in order to understand and utilize the effects of small compounds, in particular, in a recently developed method to decompose multiple effects of a drug.

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Short Keynote Paper: Mainstreaming Personalized Healthcare-Transforming Healthcare through new era of Artificial Intelligence

Cited by 35 publications

References 37 publications

Survey on 6G Frontiers: Trends, Applications, Requirements, Technologies and Future Research

Survey on 6G Frontiers: Trends, Applications, Requirements, Technologies and Future Research

Artificial Intelligence at Healthcare Industry

Interesting Properties of Profile Data Analysis in the Understanding and Utilization of the Effects of Drugs

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