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Sep 2025 DOI 10.14302/issn.2768-0207.jbr-25-5706
Nakamura YusukeCorresponding author
Artificial Intelligence (AI) is emerging as a transformative force across many sectors, with healthcare representing both one of the most promising and most challenging areas of application. This review summarizes current and future applications of AI in healthcare, focusing on its potential to improve diagnosis, therapy, chronic disease management, and overall patient care, while also alleviating physicians’ workload. Recent literature demonstrates that AI systems can reduce diagnostic errors/delays by mitigating cognitive biases, support imaging and pathology through improved accuracy and speed, and prevent prescribing errors by integrating pharmacogenomic and clinical data into decision-support systems. In chronic disease management, AI-powered wearable devices enable continuous monitoring and early detection of conditions such as atrial fibrillation, thereby reducing the risk of stroke and long-term disability, particularly in elderly people. Therapeutic applications include AI-driven drug discovery, personalized oncology, and tailored medicine that integrates multi-omics and lifestyle data. Beyond direct medical intervention, AI contributes by automating routine tasks, optimizing workflows, and facilitating greater patient–clinician interaction. Despite these benefits, significant challenges remain, including issues of data quality, privacy, security, equity, and the need for transparency and trust in “black box” systems. Looking ahead, the integration of multimodal data, digital twins, and robotics is expected to advance more comprehensive, equitable, and human-centered care. We conclude that, when applied ethically and responsibly, AI should not replace clinicians but rather serve as a powerful partner that enhances medicine by restoring empathy and humanity.
Oct 2021 DOI 10.14302/issn.2641-5526.jmid-21-3900
Perez Jean-claudeCorresponding author
Phd Maths Computer Science Bordeaux University, RETIRED Interdisciplinary Researcher (IBM Emeritus, IBM European Research Center On Artificial Intelligence Montpellier) Bordeaux Metropole, France.
In this theoretical discovery of a law of Life, there is MATHEMATICS (Geometry, Bits and Numbers) that UNIFY 3 universes as complementary as ATOMIC MASS, WAVES, and INFORMATION (DNA, RNA and Amino Acids). The discovery of a simple numerical formula for the projection of all the atomic mass of life-sustaining CONHSP bioatoms leads to the emergence of a set of Nested CODES unifying all the biological, genetic and genomic components by unifying them from bioatoms up to 'to whole genomes. In particular, we demonstrate the existence of a digital meta-code common to the three languages of biology that are RNA, DNA and amino acid sequences. Through this meta-code, genomic and proteomic images appear almost analogous and correlated. The analysis of the textures of these images then reveals a binary code as well as an undulatory code whose analysis on the human genome makes it possible to predict the alternating bands constituting the cariotypes of the chromosomes. The application of these codes to perspectives in astrobiology, cancer, and specifically in INFORMATION THEORY with the emergence of binary codes and regions of local stability (voting process), whose fractal nature we demonstrate, is illustrated. PREFACE by Professor Luc Montagnier Addendum by Robert Friedman M.D After the discovery of the DNA double helix structure allowing both the stable storage of genetic information and its transfer through messenger RNA to protein synthesis organelles themselves structured by RNA most abundant in cells, the ribosomal. This wonder of nature exists in ALL living beings from the virus to humans and is based on two codes, the linear sequence of nucleotides and that derived from codons where three nucleotides allow with a certain flexibility - synonymous codons - the choice in the twenty amino acids. But we are missing a third CODE the one governing at multicellular beings from the rotifer to human, the stabilized modulation of gene expression in a nutshell the differentiation of cells from the single cell of the fertilized egg. It is logical to think that this program which begins as soon as fertilization is written in the DNA. We are also prone to associate it with non-coding DNA sequences although they control gene expression. I introduce here the notion developed by Jean-Claude Pérez of mathematical harmony, a higher order present in all living beings and whose existence it finds in genomes, including those of viruses. Thus the natural evolution of variants of the genome of coronavirus Covid 19 tends towards increasingly long Fibonacci series. It remains to determine the Who, the How and the Why of such developments. I will bet with my mathematician colleague that waves and fractals play a role. Luc Montagnier ADDENDUM Jean-claude has given scientists a strong new direction for research. He has identified a unified field of science guided by the Golden Ratio and Fibonacci Sequence. By identifying an overall guiding principle that makes possible fractal-like nesting at all levels of biological manifestation, future researchers can begin with the "whole" instead of the "parts". If we know that complex systems are organized at varying levels by the Golden Ratio and Fibonacci Sequence, we can look for those universal patterns first and then fill in the gaps with small details to complete the picture. It's like having an overall view of a crossword puzzle before beginning to assemble the individual pieces. Without an overarching vision and guiding principle, completing the puzzle is infinitely more difficult. Once scientists and researchers realize and begin using this "SECRET IN HIDDEN IN PLAIN SIGHT," their discoveries will be orders of magnitude more fruitful. Robert Friedman M.D
Dec 2020 DOI 10.14302/issn.2641-4538.jphi-20-3427
K. Langat SimonCorresponding author
Automation of human tasks has taken place for a long time now. Humans have in earlier periods dreamed of a world where machines capable of mimicking decision making would be created with some works of fiction describing in caricature, how machines would take over the human space in the world. Artificial intelligence has come to fruition in the last few decades following the development of fast computing capability and vast chip memory. Discussions of how the human space will look and feel when artificial intelligence have taken place at various levels of global organization geared towards ensuring that the new “thinking machines” do not rock human society in ways to render them obsolete. This article looks at the ethics of AI considering the issues that have been outlined by others in the light of communitarian ethics as seen in Africa. It describes the possible impact of thinking machines on society and how individuals would relate with each other and with AI systems.
Mar 2019 DOI 10.14302/issn.2643-2811.jmbr-19-2659
C LangenhanCorresponding author
Technische Universität München
As the complexity of building tasks and requirements increases, designers often find themselves confronted with interdisciplinary problems that go beyond the specific challenges and methods of architecture. The iterative nature of the design process results in a continuous exchange between creative, analytical and evaluative activities, through which the designer explores and identifies promising design variants. The ability to compare and evaluate relevant reference examples of already built or designed buildings helps designers to assess their own design and informs the design process.
May 2024 DOI 10.14302/issn.2998-1506.jpa-24-5058
Shrestha SwatiCorresponding author
Wheat is a staple grain crop in the United States and around the world. Weed infestation, particularly grass weeds, poses significant challenges to wheat production, competing for resources and reducing grain yield and quality. Effective weed management practices, including early identification and targeted herbicide application are essential to avoid economic losses. Recent advancements in unmanned aerial vehicles (UAVs) and artificial intelligence (AI), offer promising solutions for early weed detection and management, improving efficiency and reducing negative environment impact. The integration of robotics and information technology has enabled the development of automated weed detection systems, reducing the reliance on manual scouting and intervention. Various sensors in conjunction with proximal and remote sensing techniques have the capability to capture detailed information about crop and weed characteristics. Additionally, multi-spectral and hyperspectral sensors have proven highly effective in weed vs crop detection, enabling early intervention and precise weed management. The data from various sensors consecutively processed with the help of machine learning and deep learning models (DL), notably Convolutional Neural Networks (CNNs) method have shown superior performance in handling large datasets, extracting intricate features, and achieving high accuracy in weed classification at various growth stages in numerous crops. However, the application of deep learning models in grass weed detection for wheat crops remains underexplored, presenting an opportunity for further research and innovation. In this review we underscore the potential of automated grass weed detection systems in enhancing weed management practices in wheat cropping systems. Future research should focus on refining existing techniques, comparing ML and DL models for accuracy and efficiency, and integrating UAV-based mapping with AI algorithms for proactive weed control strategies. By harnessing the power of AI and machine learning, automated weed detection holds the key to sustainable and efficient weed management in wheat cropping systems.
Dec 2023 DOI 10.14302/issn.2766-8681.jcsr-23-4811
Isea RaúlCorresponding author
Biotechnology has changed our relationships and perspectives of the world, influencing industry and serving as a catalyst for scientific discoveries. With this change, biotechnology enters a new age known as Biotechnology 2.0. "Modern Biotechnology" and "Artificial Intelligence" are getting married. In order to lessen food poverty, this idea incorporates the most recent advancements in genetic engineering, medicine, environmental preservation, and agricultural productivity and loss reduction strategies. The importance of openness and public involvement in addressing public concerns and advancing moral behavior in biotechnology's future, fostering cooperation among diverse stakeholders, and accomplishing this in a sustainable way for the good of society and humanity cannot be overstated, especially with the backing of biotechnology governance.
Jun 2023 DOI 10.14302/issn.2692-1537.ijcv-23-4586
Isea RaúlCorresponding author
The goal is to do a text mining analysis of all scientific publications and find out what journal and what aspects are studying about the conspiracy theories of Covid-19. For this purpose, all publications available in the National Center for Biotechnology Information (NCBI) database were consulted as they were peer-reviewed papers. Of all these papers, only the abstracts of each one were studied using artificial intelligence techniques to determine, for example, whether the subject is of importance depending on the journals where it has been published, and above all, what possible relationships could be extracted from the information published in them. In addition, the "Net Prevalence per Covid19" index was definedin those countries with a high value, greater campaigns should be sponsored to avoid the misinformation generated by Covid-19, although this comment should be verified in future publications. The main challenge was to unify the abstracts and for this purpose, a text summarizer was used under artificial intelligence schemes. The results obtained indicate the tendency of certain topics by the frequency of the words obtained where the focus on the conspiration are the Covid-19 vaccines, but further work is still needed to continue working on this methodology to unify the results.
Jun 2023 DOI 10.14302/issn.2766-8681.jcsr-23-4526
Isea RaúlCorresponding author
A large volume of data is being generated in public administration and it is necessary to develop new computational methodologies to classify and analyze it to do a better analysis and decision making. For this reason, the goal of this paper is to present a computational methodology that allows classifying and prioritizing a series of complaints using Artificial Intelligence techniques. To test this model, we generate 600 complaints in four sectors of the public administration to prove the concept. Later, we calculated the tree decision with the help of the Confusion Matrix, and finally the Priority Matrix (based on the Eisenhower model) allows setting priorities on the complaints, and offers the possibility of delegating and even postponing the response to them. In this way, it is possible to prioritize the complaints made in the public administration.
Jan 2019 DOI 10.14302/issn.2643-2811.jmbr-18-2539
Shaikh SadiqueCorresponding author
KYDSC Trust’s, Institute of Management & Science (IMS), Bhusawal, M.S, India
In this work, we try to explain the concept of human talent with the help of some equations and models, which are not generated by any one previously. Here we also trying to explain ‘human talent is not resources it’s itself one of the great sources to find out all possible resources’. Because we cannot predict human talent directly, to judge it, we should have to adapt some methods for talent acquisition, which we explained with the help of models and equations. How human talent is one of the great source, if we want to know it, we have to observe human behavior, wits and intelligence strictly by working simultaneously with them. In this work our conclusion is ‘human talent natural and dynamic in nature’ and can be easily diverted to perform any task. Where as machine and technology has programmed memory, logics i.e. artificial intelligence (AI), and hence in result talent is fixed and constant in nature and only able to do repetitive and fixed task and also for proper handling and utilization of machines and technology need arises of human talent. In last only want to mentioned work is very useful in all HRM and OB practices.