Application of Artificial Intelligence in Pharmaceutical and Biomedical Studies

Background: Artificial intelligence (AI) is the way to model human intelligence to accomplish certain tasks without much intervention of human beings. The term AI was first used in 1956 with The Logic Theorist program, which was designed to simulate problem-solving ability of human beings. There have been a significant amount of research works using AI in order to determine the advantages and disadvantages of its applicabication and, future perspectives that impact different areas of society. Even the remarkable impact of AI can be transferred to the field of healthcare with its use in pharmaceutical and biomedical studies crucial for the socioeconomic development of the population in general within different studies, we can highlight those that have been conducted with the objective of treating diseases, such as cancer, neurodegenerative diseases, among others. In parallel, the long process of drug development also requires the application of AI to accelerate research in medical care. Methods: This review is based on research material obtained from PubMed up to Jan 2020. The search terms include “artificial intelligence”, “machine learning” in the context of research on pharmaceutical and biomedical applications. Results: This study aimed to highlight the importance of AI in the biomedical research and also recent studies that support the use of AI to generate tools using patient data to improve outcomes. Other studies have demonstrated the use of AI to create prediction models to determine response to cancer treatment. Conclusion: The application of AI in the field of pharmaceutical and biomedical studies has been extensive, including cancer research, for diagnosis as well as prognosis of the disease state. It has become a tool for researchers in the management of complex data, ranging from obtaining complementary results to conventional statistical analyses. AI increases the precision in the estimation of treatment effect in cancer patients and determines prediction outcomes.

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An explanation of the relationship between artificial intelligence and human beings from the perspective of consciousness

Cultures of Science ◽

10.1177/20966083211056376 ◽

2021 ◽

pp. 209660832110563

Author(s):

Jianhua Xie

Keyword(s):

Artificial Intelligence ◽

Virtue Ethics ◽

Moral Status ◽

Contract Theory ◽

Human Beings ◽

Evolution Of Consciousness ◽

Advantages And Disadvantages ◽

Development Level ◽

Normative Significance ◽

The Relationship

What will be the relationship between human beings and artificial intelligence (AI) in the future? Does an AI have moral status? What is that status? Through the analysis of consciousness, we can explain and answer such questions. The moral status of AIs can depend on the development level of AI consciousness. Drawing on the evolution of consciousness in nature, this paper examines several consciousness abilities of AIs, on the basis of which several relationships between AIs and human beings are proposed. The advantages and disadvantages of those relationships can be analysed by referring to classical ethics theories, such as contract theory, utilitarianism, deontology and virtue ethics. This explanation helps to construct a common hypothesis about the relationship between humans and AIs. Thus, this research has important practical and normative significance for distinguishing the different relationships between humans and AIs.

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Comparison of Dual Beam Dispersive and FTNIR Spectroscopy for Lactate Detection

Sensors ◽

10.3390/s21051891 ◽

2021 ◽

Vol 21 (5) ◽

pp. 1891

Author(s):

Nystha Baishya ◽

Mohammad Mamouei ◽

Karthik Budidha ◽

Meha Qassem ◽

Pankaj Vadgama ◽

...

Keyword(s):

Biomedical Applications ◽

Near Infrared ◽

Prediction Models ◽

Full Range ◽

Multivariate Techniques ◽

Analyte Concentration ◽

Predictive Capability ◽

Advantages And Disadvantages ◽

Dual Beam

Near Infrared (800–2500 nm) spectroscopy has been extensively used in biomedical applications, as it offers rapid, in vivo, bed-side monitoring of important haemodynamic parameters, which is especially important in critical care settings. However, the choice of NIR spectrometer needs to be investigated for biomedical applications, as both the dual beam dispersive spectrophotomer and the FTNIR spectrometer have their own advantages and disadvantages. In this study, predictive analysis of lactate concentrations in whole blood were undertaken using multivariate techniques on spectra obtained from the two spectrometer types simultaneously and results were compared. Results showed significant improvement in predicting analyte concentration when analysis was performed on full range spectral data. This is in comparison to analysis of limited spectral regions or lactate signature peaks, which yielded poorer prediction models. Furthermore, for the same region, FTNIR showed 10% better predictive capability than the dual beam dispersive NIR spectrometer.

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Decision Tree in Biology

European Journal of Biology ◽

10.47672/ejb.642 ◽

2021 ◽

Vol 6 (1) ◽

pp. 1-15

Author(s):

Komal Shazadi

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Medical Information ◽

Prediction Models ◽

Biological Research ◽

Complex Data ◽

Adequate Care ◽

Biological Studies ◽

Wide Range ◽

Care Technology

Purpose: Human biology is an essential field in scientific research as it helps in understanding the human body for adequate care. Technology has improved the way scientists do their biological research. One of the critical technologies is artificial intelligence (AI), which is revolutionizing the world. Scientists have applied AI in biological studies, using several methods to gain different types of data. Machine learning is a branch of artificial intelligence that helps computers learn from data and create predictions without being explicitly programmed. Methodology: One critical methodology in the machine is using the tree-based decision. It is extensively used in biological research, as it helps in classifying complex data into simple and easy to interpret graphs. This paper aims to give a beginner-friendly view of the tree-based model, analyzing its use and advantages over other methods. Finding: Artificial intelligence has greatly improved the collection, analysis, and prediction of biological and medical information. Machine learning, a subgroup of artificial intelligence, is useful in creating prediction models, which help a wide range of fields, including computational and systems biology. Contribution and future recommendation also discussed in this study.

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Artificial intelligence and colonoscopy: Current status and future perspectives

Digestive Endoscopy ◽

10.1111/den.13340 ◽

2019 ◽

Vol 31 (4) ◽

pp. 363-371 ◽

Cited By ~ 32

Author(s):

Shin‐ei Kudo ◽

Yuichi Mori ◽

Masashi Misawa ◽

Kenichi Takeda ◽

Toyoki Kudo ◽

...

Keyword(s):

Artificial Intelligence ◽

Current Status ◽

Future Perspectives

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How to Improve Physico-Chemical Properties of Silk Fibroin Materials for Biomedical Applications?—Blending and Cross-Linking of Silk Fibroin—A Review

Materials ◽

10.3390/ma14061510 ◽

2021 ◽

Vol 14 (6) ◽

pp. 1510

Author(s):

Sylwia Grabska-Zielińska ◽

Alina Sionkowska

Keyword(s):

Silk Fibroin ◽

Biomedical Applications ◽

Magnetic Particles ◽

Chemical Properties ◽

Ternary Mixtures ◽

Cross Linking ◽

Advantages And Disadvantages ◽

Physico Chemical ◽

Binary And Ternary Mixtures ◽

To Receive

This review supplies a report on fresh advances in the field of silk fibroin (SF) biopolymer and its blends with biopolymers as new biomaterials. The review also includes a subsection about silk fibroin mixtures with synthetic polymers. Silk fibroin is commonly used to receive biomaterials. However, the materials based on pure polymer present low mechanical parameters, and high enzymatic degradation rate. These properties can be problematic for tissue engineering applications. An increased interest in two- and three-component mixtures and chemically cross-linked materials has been observed due to their improved physico-chemical properties. These materials can be attractive and desirable for both academic, and, industrial attention because they expose improvements in properties required in the biomedical field. The structure, forms, methods of preparation, and some physico-chemical properties of silk fibroin are discussed in this review. Detailed examples are also given from scientific reports and practical experiments. The most common biopolymers: collagen (Coll), chitosan (CTS), alginate (AL), and hyaluronic acid (HA) are discussed as components of silk fibroin-based mixtures. Examples of binary and ternary mixtures, composites with the addition of magnetic particles, hydroxyapatite or titanium dioxide are also included and given. Additionally, the advantages and disadvantages of chemical, physical, and enzymatic cross-linking were demonstrated.

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Nanoengineering in biomedicine: Current development and future perspectives

Nanotechnology Reviews ◽

10.1515/ntrev-2020-0053 ◽

2020 ◽

Vol 9 (1) ◽

pp. 700-715 ◽

Cited By ~ 1

Author(s):

Wei Jian ◽

David Hui ◽

Denvid Lau

Keyword(s):

Molecular Dynamics ◽

Research And Development ◽

Molecular Dynamics Simulations ◽

Material Properties ◽

Biomedical Applications ◽

Metallic Materials ◽

Future Perspectives ◽

Current Development ◽

Materials Used ◽

Dynamics Simulations

AbstractRecent advances in biomedicine largely rely on the development in nanoengineering. As the access to unique properties in biomaterials is not readily available from traditional techniques, the nanoengineering becomes an effective approach for research and development, by which the performance as well as the functionalities of biomaterials has been greatly improved and enriched. This review focuses on the main materials used in biomedicine, including metallic materials, polymers, and nanocomposites, as well as the major applications of nanoengineering in developing biomedical treatments and techniques. Research that provides an in-depth understanding of material properties and efficient enhancement of material performance using molecular dynamics simulations from the nanoengineering perspective are discussed. The advanced techniques which facilitate nanoengineering in biomedical applications are also presented to inspire further improvement in the future. Furthermore, the potential challenges of nanoengineering in biomedicine are evaluated by summarizing concerned issues and possible solutions.

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Evaluation of offshore wind power in the China sea

Energy Exploration & Exploitation ◽

10.1177/0144598721992268 ◽

2021 ◽

pp. 014459872199226

Author(s):

Yu-chi Tian ◽

Lei kou ◽

Yun-dong Han ◽

Xiaodong Yang ◽

Ting-ting Hou ◽

...

Keyword(s):

Wind Energy ◽

Wind Power ◽

Energy Development ◽

Offshore Wind ◽

Human Beings ◽

Offshore Wind Power ◽

Business Operation ◽

Advantages And Disadvantages ◽

Wind Energy Development ◽

The Impact

With resource crisis and environmental crisis increasingly grim, many countries turn the focus to pollution-free and renewable wind energy resources, which are mainly used for offshore wind power generation, seawater desalination and heating, etc., on the premise that the characteristics of resources are fully grasped. In this study, the evaluation of offshore wind energy in offshore waters in China, as well as the advantages and disadvantages of existing studies were overviewed from four aspects: the spatial-temporal characteristics of wind energy, wind energy classification, the short-term forecast of wind energy and the long-term projection of wind energy, according to the research content and the future considerations about wind energy evaluation (evaluation of wind energy on islands and reefs, the impact of wind energy development on human health) were envisaged, in the hope of providing a scientific basis for the site selection and business operation ‘or military applications’ here (after business operation), etc. of wind energy development, ‘aritime navigation against environmental construction,’ here and also contributing to the sustainable development and health of human beings.

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Prediction Models for Public Health Containment Measures on COVID-19 Using Artificial Intelligence and Machine Learning: A Systematic Review

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18094499 ◽

2021 ◽

Vol 18 (9) ◽

pp. 4499

Author(s):

Anil Babu Payedimarri ◽

Diego Concina ◽

Luigi Portinale ◽

Massimo Canonico ◽

Deborah Seys ◽

...

Keyword(s):

Public Health ◽

Artificial Intelligence ◽

Machine Learning ◽

Systematic Review ◽

Public Transportation ◽

Prediction Models ◽

Positive Impact ◽

Health Interventions ◽

Public Health Interventions ◽

Commercial Activities

Artificial Intelligence (AI) and Machine Learning (ML) have expanded their utilization in different fields of medicine. During the SARS-CoV-2 outbreak, AI and ML were also applied for the evaluation and/or implementation of public health interventions aimed to flatten the epidemiological curve. This systematic review aims to evaluate the effectiveness of the use of AI and ML when applied to public health interventions to contain the spread of SARS-CoV-2. Our findings showed that quarantine should be the best strategy for containing COVID-19. Nationwide lockdown also showed positive impact, whereas social distancing should be considered to be effective only in combination with other interventions including the closure of schools and commercial activities and the limitation of public transportation. Our findings also showed that all the interventions should be initiated early in the pandemic and continued for a sustained period. Despite the study limitation, we concluded that AI and ML could be of help for policy makers to define the strategies for containing the COVID-19 pandemic.

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The perception of humanness in conversational journalism: An algorithmic information-processing perspective

New Media & Society ◽

10.1177/1461444821993801 ◽

2021 ◽

pp. 146144482199380

Author(s):

Donghee Shin

Keyword(s):

Artificial Intelligence ◽

Information Processing ◽

Cognitive Model ◽

Human Beings ◽

User Perception ◽

User Experiences ◽

Step Flow ◽

Algorithmic Information ◽

Information Processing Perspective ◽

Practical Implications

How much do anthropomorphisms influence the perception of users about whether they are conversing with a human or an algorithm in a chatbot environment? We develop a cognitive model using the constructs of anthropomorphism and explainability to explain user experiences with conversational journalism (CJ) in the context of chatbot news. We examine how users perceive anthropomorphic and explanatory cues, and how these stimuli influence user perception of and attitudes toward CJ. Anthropomorphic explanations of why and how certain items are recommended afford users a sense of humanness, which then affects trust and emotional assurance. Perceived humanness triggers a two-step flow of interaction by defining the baseline to make a judgment about the qualities of CJ and by affording the capacity to interact with chatbots concerning their intention to interact with chatbots. We develop practical implications relevant to chatbots and ascertain the significance of humanness as a social cue in CJ. We offer a theoretical lens through which to characterize humanness as a key mechanism of human–artificial intelligence (AI) interaction, of which the eventual goal is humans perceive AI as human beings. Our results help to better understand human–chatbot interaction in CJ by illustrating how humans interact with chatbots and explaining why humans accept the way of CJ.

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A review of flexible electric heating element and electric heating garments

Journal of Industrial Textiles ◽

10.1177/1528083720968278 ◽

2020 ◽

pp. 152808372096827

Author(s):

Shu Fang ◽

Rui Wang ◽

Haisu Ni ◽

Hao Liu ◽

Li Liu

Keyword(s):

Electric Heating ◽

Review Article ◽

Electrical Heating ◽

Cold Environment ◽

Passive Heating ◽

Future Perspectives ◽

Advantages And Disadvantages ◽

Smart Garments ◽

Material Preparation ◽

Electric Heating Element

Electric heating garment can improve the thermal comfort for people living and working in cold environment. Compared with passive heating materials, electrical heating shows dominant advantages on reusability, controlled temperature, safety and so on. This review article systematically introduced the material preparation, electric-thermal properties, advantages and disadvantages of the existing flexible heating elements, and elaborated the research and application progress of smart garments in detail, providing reference for the research of flexible heating elements and smart garments. And the existing challenges and the possible future perspectives were also discussed.

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