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The Science of the Total Environment Aug 2023Carbon capturing is imperative to fight climate change as much carbon emissions are liberated into the atmosphere, leading to adversely negative environmental impacts.... (Review)
Review
Carbon capturing is imperative to fight climate change as much carbon emissions are liberated into the atmosphere, leading to adversely negative environmental impacts. Today's world addresses all the issues with the aid of digital technologies like data pooling and artificial intelligence (AI). Accordingly, this study is articulated based on AI-assisted carbon capturing. Techniques including machine learning (ML), deep learning (DL), and hybrid techniques being adopted in carbon capture are discussed. The role of AI tools, frameworks, and mathematical models are also discussed herein. Furthermore, the confluence of AI in carbon capture patent landscape is explored. This study would allow researchers to envision the growth of AI-assisted carbon capture in mitigating climate change and meeting SDG 13 - climate action.
Topics: Artificial Intelligence; Machine Learning
PubMed: 37150463
DOI: 10.1016/j.scitotenv.2023.163913 -
Sovremennye Tekhnologii V Meditsine 2023Surgery performed by a novice neurosurgeon under constant supervision of a senior surgeon with the experience of thousands of operations, able to handle any... (Review)
Review
Surgery performed by a novice neurosurgeon under constant supervision of a senior surgeon with the experience of thousands of operations, able to handle any intraoperative complications and predict them in advance, and never getting tired, is currently an elusive dream, but can become a reality with the development of artificial intelligence methods. This paper has presented a review of the literature on the use of artificial intelligence technologies in the microsurgical operating room. Searching for sources was carried out in the PubMed text database of medical and biological publications. The key words used were "surgical procedures", "dexterity", "microsurgery" AND "artificial intelligence" OR "machine learning" OR "neural networks". Articles in English and Russian were considered with no limitation to publication date. The main directions of research on the use of artificial intelligence technologies in the microsurgical operating room have been highlighted. Despite the fact that in recent years machine learning has been increasingly introduced into the medical field, a small number of studies related to the problem of interest have been published, and their results have not proved to be of practical use yet. However, the social significance of this direction is an important argument for its development.
Topics: Operating Rooms; Artificial Intelligence; Neural Networks, Computer; Machine Learning; Intelligence
PubMed: 37389018
DOI: 10.17691/stm2023.15.2.08 -
Archivos de Bronconeumologia Feb 2021
Topics: Artificial Intelligence; Humans; Machine Learning; Respiration Disorders
PubMed: 32081439
DOI: 10.1016/j.arbres.2019.12.037 -
Trends in Biotechnology Apr 2023Artificial intelligence and machine learning (AI-ML) offer vast potential in optimal design, monitoring, and control of biopharmaceutical manufacturing. The driving... (Review)
Review
Artificial intelligence and machine learning (AI-ML) offer vast potential in optimal design, monitoring, and control of biopharmaceutical manufacturing. The driving forces for adoption of AI-ML techniques include the growing global demand for biotherapeutics and the shift toward Industry 4.0, spurring the rise of integrated process platforms and continuous processes that require intelligent, automated supervision. This review summarizes AI-ML applications in biopharmaceutical manufacturing, with a focus on the most used AI-ML algorithms, including multivariate data analysis, artificial neural networks, and reinforcement learning. Perspectives on the future growth of AI-ML applications in the area and the challenges of implementing these techniques at manufacturing scale are also presented.
Topics: Artificial Intelligence; Biological Products; Machine Learning; Neural Networks, Computer; Algorithms
PubMed: 36117026
DOI: 10.1016/j.tibtech.2022.08.007 -
Oral and Maxillofacial Surgery Clinics... Nov 2022Artificial intelligence has become ubiquitous with modern technology. Digital transformations are occurring in every field including medicine, surgery, and education.... (Review)
Review
Artificial intelligence has become ubiquitous with modern technology. Digital transformations are occurring in every field including medicine, surgery, and education. Computers and computer programs are getting sophisticated to form neural networks globally. These algorithms allow for sophisticated and complex pattern recognitions and make accurate predictions. This allows for both accurate diagnosis and prognostication in medicine and opens opportunities for medical and surgical education. Oral and Maxillofacial surgeons and OMS education like all of the surgery are adapting well to the world of AI, incorporating machine learning into simulation, and attaching sensors to master surgeons to understand motion economy.
Topics: Humans; Artificial Intelligence; Algorithms; Neural Networks, Computer; Machine Learning; Surgery, Oral
PubMed: 36224076
DOI: 10.1016/j.coms.2022.03.006 -
The British Journal of Radiology Apr 2022Artificial intelligence (AI) is transforming the way we perform advanced imaging. From high-resolution image reconstruction to predicting functional response from... (Review)
Review
Artificial intelligence (AI) is transforming the way we perform advanced imaging. From high-resolution image reconstruction to predicting functional response from clinically acquired data, AI is promising to revolutionize clinical evaluation of lung performance, pushing the boundary in pulmonary functional imaging for patients suffering from respiratory conditions. In this review, we overview the current developments and expound on some of the encouraging new frontiers. We focus on the recent advances in machine learning and deep learning that enable reconstructing images, quantitating, and predicting functional responses of the lung. Finally, we shed light on the potential opportunities and challenges ahead in adopting AI for functional lung imaging in clinical settings.
Topics: Artificial Intelligence; Deep Learning; Diagnostic Imaging; Humans; Lung; Machine Learning
PubMed: 34890215
DOI: 10.1259/bjr.20210527 -
Nutrients Jan 2021Artificial intelligence (AI) as a branch of computer science, the purpose of which is to imitate thought processes, learning abilities and knowledge management, finds... (Review)
Review
Artificial intelligence (AI) as a branch of computer science, the purpose of which is to imitate thought processes, learning abilities and knowledge management, finds more and more applications in experimental and clinical medicine. In recent decades, there has been an expansion of AI applications in biomedical sciences. The possibilities of artificial intelligence in the field of medical diagnostics, risk prediction and support of therapeutic techniques are growing rapidly. The aim of the article is to analyze the current use of AI in nutrients science research. The literature review was conducted in PubMed. A total of 399 records published between 1987 and 2020 were obtained, of which, after analyzing the titles and abstracts, 261 were rejected. In the next stages, the remaining records were analyzed using the full-text versions and, finally, 55 papers were selected. These papers were divided into three areas: AI in biomedical nutrients research (20 studies), AI in clinical nutrients research (22 studies) and AI in nutritional epidemiology (13 studies). It was found that the artificial neural network (ANN) methodology was dominant in the group of research on food composition study and production of nutrients. However, machine learning (ML) algorithms were widely used in studies on the influence of nutrients on the functioning of the human body in health and disease and in studies on the gut microbiota. Deep learning (DL) algorithms prevailed in a group of research works on clinical nutrients intake. The development of dietary systems using AI technology may lead to the creation of a global network that will be able to both actively support and monitor the personalized supply of nutrients.
Topics: Artificial Intelligence; Biomedical Research; Humans; Machine Learning; Neural Networks, Computer; Nutrients
PubMed: 33499405
DOI: 10.3390/nu13020322 -
Journal of Oral Pathology & Medicine :... Oct 2020Recently, there has been a momentous drive to apply advanced artificial intelligence (AI) technologies to diagnostic medicine. The introduction of AI has provided vast... (Review)
Review
BACKGROUND
Recently, there has been a momentous drive to apply advanced artificial intelligence (AI) technologies to diagnostic medicine. The introduction of AI has provided vast new opportunities to improve health care and has introduced a new wave of heightened precision in oncologic pathology. The impact of AI on oncologic pathology has now become apparent, and its use with respect to oral oncology is still in the nascent stage.
DISCUSSION
A foundational overview of AI classification systems used in medicine and a review of common terminology used in machine learning and computational pathology will be presented. This paper provides a focused review on the recent advances in AI and deep learning in oncologic histopathology and oral oncology. In addition, specific emphasis on recent studies that have applied these technologies to oral cancer prognostication will also be discussed.
CONCLUSION
Machine and deep learning methods designed to enhance prognostication of oral cancer have been proposed with much of the work focused on prediction models on patient survival and locoregional recurrences in patients with oral squamous cell carcinomas (OSCC). Few studies have explored machine learning methods on OSCC digital histopathologic images. It is evident that further research at the whole slide image level is needed and future collaborations with computer scientists may progress the field of oral oncology.
Topics: Artificial Intelligence; Deep Learning; Humans; Machine Learning; Neoplasm Recurrence, Local
PubMed: 32449232
DOI: 10.1111/jop.13042 -
Journal of Gynecology Obstetrics and... Jan 2021Artificial Intelligence (AI), a concept which dates back to the 1950s, is increasingly being developed by many medical specialties, especially those based on imaging or... (Review)
Review
Artificial Intelligence (AI), a concept which dates back to the 1950s, is increasingly being developed by many medical specialties, especially those based on imaging or surgery. While the cognitive component of AI is far superior to that of human intelligence, it lacks consciousness, feelings, intuition and adaptation to unexpected situations. Furthermore, fundamental questions arise with regard to data security, the impact on healthcare professions, and the distribution of roles between physicians and AI especially concerning consent to medical care and liability in the event of a therapeutic accident.
Topics: Artificial Intelligence; Humans; Medicine
PubMed: 33148398
DOI: 10.1016/j.jogoh.2020.101962 -
Neurosurgery Clinics of North America Apr 2024The amount and quality of data being used in our everyday lives continue to advance in an unprecedented pace. This digital revolution has permeated healthcare,... (Review)
Review
The amount and quality of data being used in our everyday lives continue to advance in an unprecedented pace. This digital revolution has permeated healthcare, specifically spine surgery, allowing for very advanced and complex computational analytics, such as artificial intelligence (AI) and machine learning (ML). The integration of these methods into clinical practice has just begun, and the following review article will describe AI/ML, demonstrate how it has been applied in adult spinal deformity surgery, and show its potential to improve patient care touching on future directions.
Topics: Humans; Artificial Intelligence; Machine Learning
PubMed: 38423741
DOI: 10.1016/j.nec.2023.11.001