A review on the role of artificial intelligence in stem cell therapy: An initiative for modern medicines

2020 ◽  
Vol 21 ◽  
Author(s):  
Pravin Shende ◽  
Nikita P. Devlekar
Keyword(s):  
Artificial Intelligence ◽  
Individual Cell ◽  
Home Automation ◽  
Science And Engineering ◽  
Prediction Of Mortality ◽  
Wide Range ◽  
Potential Applications ◽  
Applications Of Ai

: Stem cells (SCs) show a wide range of applications in the treatment of numerous diseases including neurodegenerative diseases, diabetes, cardiovascular diseases, cancer, etc. SC related research has gained popularity owing to the unique characteristics of self-renewal and differentiation. Artificial intelligence (AI), an emerging field of computer science and engineering has shown potential applications in different fields like robotics, agriculture, home automation, healthcare, banking, and transportation since its invention. This review aims to describe the various applications of AI in SC biology including understanding the behavior of SCs, recognizing individual cell type before undergoing differentiation, characterization of SCs using mathematical models and prediction of mortality risk associated with SC transplantation. This review emphasizes the role of neural networks in SC biology and further elucidates the concepts of machine learning and deep learning and their applications in SC research.

scholarly journals Applications of Artificial Intelligence for the Diagnosis of Gastrointestinal Diseases

Diagnostics ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1575
Author(s):  
Silvia Pecere ◽  
Sebastian Manuel Milluzzo ◽  
Gianluca Esposito ◽  
Emanuele Dilaghi ◽  
Andrea Telese ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Health Care Professionals ◽  
Gastrointestinal Diseases ◽  
Controlled Trials ◽  
Clinical Settings ◽  
High Quality ◽  
Potential Applications ◽  
Malignant Lesions ◽  
Applications Of Ai

The development of convolutional neural networks has achieved impressive advances of machine learning in recent years, leading to an increasing use of artificial intelligence (AI) in the field of gastrointestinal (GI) diseases. AI networks have been trained to differentiate benign from malignant lesions, analyze endoscopic and radiological GI images, and assess histological diagnoses, obtaining excellent results and high overall diagnostic accuracy. Nevertheless, there data are lacking on side effects of AI in the gastroenterology field, and high-quality studies comparing the performance of AI networks to health care professionals are still limited. Thus, large, controlled trials in real-time clinical settings are warranted to assess the role of AI in daily clinical practice. This narrative review gives an overview of some of the most relevant potential applications of AI for gastrointestinal diseases, highlighting advantages and main limitations and providing considerations for future development.

scholarly journals Role of Artificial Intelligence in Fighting Antimicrobial Resistance in Pediatrics

Antibiotics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 767 ◽  
Author(s):  
Umberto Fanelli ◽  
Marco Pappalardo ◽  
Vincenzo Chinè ◽  
Pierpacifico Gismondi ◽  
Cosimo Neglia ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Antimicrobial Resistance ◽  
Antimicrobial Stewardship ◽  
Potential Role ◽  
Antimicrobial Agents ◽  
Primary Role ◽  
Science And Engineering ◽  
Intelligent Behavior ◽  
Applications Of Ai

Artificial intelligence (AI) is a field of science and engineering concerned with the computational understanding of what is commonly called intelligent behavior. AI is extremely useful in many human activities including medicine. The aim of our narrative review is to show the potential role of AI in fighting antimicrobial resistance in pediatric patients. We searched for PubMed articles published from April 2010 to April 2020 containing the keywords “artificial intelligence”, “machine learning”, “antimicrobial resistance”, “antimicrobial stewardship”, “pediatric”, and “children”, and we described the different strategies for the application of AI in these fields. Literature analysis showed that the applications of AI in health care are potentially endless, contributing to a reduction in the development time of new antimicrobial agents, greater diagnostic and therapeutic appropriateness, and, simultaneously, a reduction in costs. Most of the proposed AI solutions for medicine are not intended to replace the doctor’s opinion or expertise, but to provide a useful tool for easing their work. Considering pediatric infectious diseases, AI could play a primary role in fighting antibiotic resistance. In the pediatric field, a greater willingness to invest in this field could help antimicrobial stewardship reach levels of effectiveness that were unthinkable a few years ago.

scholarly journals Focused ultrasound in neuro-oncology: the role of the Focused Ultrasound Foundation in driving adoption and innovation

2021 ◽  
Author(s):  
Emily C. Whipple ◽  
Camille A. Favero ◽  
Neal F. Kassell
Keyword(s):  
Drug Delivery ◽  
Brain Tumors ◽  
Focused Ultrasound ◽  
Clinical Evidence ◽  
Neurological Injury ◽  
High Concentration ◽  
Potential Applications ◽  
Tumor Agent

Abstract Introduction Intra-arterial (lA) delivery of therapeutic agents across the blood-brain barrier (BBB) is an evolving strategy which enables the distribution of high concentration therapeutics through a targeted vascular territory, while potentially limiting systemic toxicity. Studies have demonstrated lA methods to be safe and efficacious for a variety of therapeutics. However, further characterization of the clinical efficacy of lA therapy for the treatment of brain tumors and refinement of its potential applications are necessary. Methods We have reviewed the preclinical and clinical evidence supporting superselective intraarterial cerebral infusion (SSJACI) with BBB disruption for the treatment of brain tumors. In addition, we review ongoing clinical trials expanding the applicability and investigating the efficacy of lA therapy for the treatment of brain tumors. Results Trends in recent studies have embraced the use of SSIACI and less neurotoxic chemotherapies. The majority of trials continue to use mannitol as the preferred method of hyperosmolar BBB disruption. Recent preclinical and preliminary human investigations into the lA delivery of Bevacizumab have demonstrated its safety and efficacy as an anti-tumor agent both alone and in combination with chemotherapy. Conclusion lA drug delivery may significantly affect the way treatment are delivered to patients with brain tumors, and in particular GBM. With refinement and standardization of the techniques of lA drug delivery, improved drug selection and formulations, and the development of methods to minimize treatment-related neurological injury, lA therapy may offer significant benefits for the treatment of brain tumors.

scholarly journals Radiology Community Attitude in Saudi Arabia about the Applications of Artificial Intelligence in Radiology

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 834
Author(s):  
Magbool Alelyani ◽  
Sultan Alamri ◽  
Mohammed S. Alqahtani ◽  
Alamin Musa ◽  
Hajar Almater ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Saudi Arabia ◽  
Vital Role ◽  
Human Machine Interaction ◽  
The Future ◽  
Level Of Knowledge ◽  
Electronic Questionnaires ◽  
Machine Interaction ◽  
Applications Of Ai

Artificial intelligence (AI) is a broad, umbrella term that encompasses the theory and development of computer systems able to perform tasks normally requiring human intelligence. The aim of this study is to assess the radiology community’s attitude in Saudi Arabia toward the applications of AI. Methods: Data for this study were collected using electronic questionnaires in 2019 and 2020. The study included a total of 714 participants. Data analysis was performed using SPSS Statistics (version 25). Results: The majority of the participants (61.2%) had read or heard about the role of AI in radiology. We also found that radiologists had statistically different responses and tended to read more about AI compared to all other specialists. In addition, 82% of the participants thought that AI must be included in the curriculum of medical and allied health colleges, and 86% of the participants agreed that AI would be essential in the future. Even though human–machine interaction was considered to be one of the most important skills in the future, 89% of the participants thought that it would never replace radiologists. Conclusion: Because AI plays a vital role in radiology, it is important to ensure that radiologists and radiographers have at least a minimum understanding of the technology. Our finding shows an acceptable level of knowledge regarding AI technology and that AI applications should be included in the curriculum of the medical and health sciences colleges.

scholarly journals Application of artificial intelligence in pancreaticobiliary diseases

2021 ◽  
Vol 14 ◽  
pp. 263177452199305
Author(s):  
Hemant Goyal ◽  
Rupinder Mann ◽  
Zainab Gandhi ◽  
Abhilash Perisetti ◽  
Zhongheng Zhang ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Response To Treatment ◽  
Endoscopic Retrograde ◽  
Artificial Intelligence Techniques ◽  
Computer Aided ◽  
Rapid Pace ◽  
Cystic Pancreatic Lesions ◽  
Aided Diagnosis

The role of artificial intelligence and its applications has been increasing at a rapid pace in the field of gastroenterology. The application of artificial intelligence in gastroenterology ranges from colon cancer screening and characterization of dysplastic and neoplastic polyps to the endoscopic ultrasonographic evaluation of pancreatic diseases. Artificial intelligence has been found to be useful in the evaluation and enhancement of the quality measure for endoscopic retrograde cholangiopancreatography. Similarly, artificial intelligence techniques like artificial neural networks and faster region-based convolution network are showing promising results in early and accurate diagnosis of pancreatic cancer and its differentiation from chronic pancreatitis. Other artificial intelligence techniques like radiomics-based computer-aided diagnosis systems could help to differentiate between various types of cystic pancreatic lesions. Artificial intelligence and computer-aided systems also showing promising results in the diagnosis of cholangiocarcinoma and the prediction of choledocholithiasis. In this review, we discuss the role of artificial intelligence in establishing diagnosis, prognosis, predicting response to treatment, and guiding therapeutics in the pancreaticobiliary system.

Electrostatically Coupled MEM Oscillators

2000 ◽  
Author(s):  
Rajashree Baskaran ◽  
Kimberly L. Turner
Keyword(s):  
System Dynamics ◽  
Electromechanical Interaction ◽  
Wide Range ◽  
Potential Applications

Abstract MicroElectroMechanical (MEM) Oscillators have a wide range of potential applications and understanding the underlying system dynamics thoroughly is essential. In this paper, we present the design, modeling and characterization of a pair of electrostatically coupled torsional oscillators fabricated with the SCREAM(1) process. The dynamic and electrostatic characteristics of the new design lead to various applications and also serve as an interesting ground for understanding the electromechanical interaction and non-linearities in MEM devices.

scholarly journals CRYOGLOBULIN TEST AND CRYOGLOBULINEMIA HEPATITIS C-VIRUS RELATED

2016 ◽  
Vol 9 (1) ◽  
pp. e2017007 ◽  
Author(s):  
Umberto Basile
Keyword(s):  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Confounding Factor ◽  
Underlying Disease ◽  
Clinical Syndrome ◽  
Laboratory Techniques ◽  
Preanalytical Phase ◽  
Wide Range

Cryoglobulins are immunoglobulins that precipitate in serum at temperatures below 37°C and resolubilize upon warming. The clinical syndrome of cryoglobulinemia usually includes purpura, weakness, and arthralgia, but the underlying disease may also contribute other symptoms. Blood samples for cryoglobulin are collected, transported, clotted and spun at 37°C, before the precipitate is allowed to form when serum is stored at 4°C in a Wintrobe tube for at least seven days. The most critical and confounding factor affecting the cryoglobulin test is when the preanalytical phase is not fully completed at 37°C. The easiest way to quantify cryoglobulins is the cryocrit estimate. However, this approach has low accuracy and sensitivity. Furthermore, the precipitate should be resolubilized by warming to confirm that it is truly formed of cryoglobulins. The characterization of cryoglobulins requires the precipitate is several times washed, before performing immunofixation, a technique by which cryoglobulins can be classified depending on the characteristics of the detected immunoglobulins. These features imply a pathogenic role of these molecules which are consequently associated with a wide range of symptoms and manifestations. According to the Brouet classification, Cryoglobulins are grouped into three types by the immunochemical properties of immunoglobulins in the cryoprecipitate. The aim of this paper is to review the major aspects of cryoglobulinemia and the laboratory techniques used to detect and characterize cryoglobulins, taking into consideration the presence and consequences of cryoglobulinemia in Hepatitis C Virus (HCV) infection.

Characterization of proteins with Siaα2-3/6Gal-linked glycans from bovine milk and role of their glycans against influenza A virus

2018 ◽  
Vol 9 (10) ◽  
pp. 5198-5208 ◽  
Author(s):  
Hanjie Yu ◽  
Yaogang Zhong ◽  
Zhiwei Zhang ◽  
Xiawei Liu ◽  
Kun Zhang ◽  
...  
Keyword(s):  
Influenza A Virus ◽  
Influenza A ◽  
Bovine Milk ◽  
Milk Proteins ◽  
Biological Functions ◽  
Wide Range ◽  
Range Of Functions ◽  
Bovine Milk Proteins

The bovine milk proteins have a wide range of functions, but the role of the attached glycans in their biological functions has not been fully understood yet.

Role of Artificial Intelligence (AI) in Surgery: Introduction, General Principles, and Potential Applications

2020 ◽  
Author(s):  
Alberto Mangano ◽  
Valentina Valle ◽  
Nicolas Dreifuss ◽  
Gabriela Aguiluz ◽  
Mario Masrur
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Tasks ◽  
Future Perspectives ◽  
General Introduction ◽  
Computing Power ◽  
Interdisciplinary Field ◽  
Potential Applications ◽  
Number Of Publications ◽  
Surgical Setting

AI (Artificial intelligence) is an interdisciplinary field aimed at the development of algorithms to endow machines with the capability of executing cognitive tasks. The number of publications regarding AI and surgery has increased dramatically over the last two decades. This phenomenon can partly be explained by the exponential growth in computing power available to the largest AI training runs. AI can be classified into different sub-domains with extensive potential clinical applications in the surgical setting. AI will increasingly become a major component of clinical practice in surgery. The aim of the present Narrative Review is to give a general introduction and summarized overview of AI, as well as to present additional remarks on potential surgical applications and future perspectives in surgery.

Applications of AI in Financial System

2017 ◽  
pp. 101-109
Author(s):  
Santosh Kumar ◽  
Roopali Sharma
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Decision Analysis ◽  
Computer Science ◽  
Investment Decision ◽  
Analysis Tool ◽  
Changing Environment ◽  
Human Interference ◽  
Applications Of Ai

Role of computers are widely accepted and well known in the domain of Finance. Artificial Intelligence(AI) methods are extensively used in field of computer science for providing solution of unpredictable event in a frequent changing environment with utilization of neural network. Professionals are using AI framework into every field for reducing human interference to get better result from few decades. The main objective of the chapter is to point out the techniques of AI utilized in field of finance in broader perspective. The purpose of this chapter is to analyze the background of AI in finance and its role in Finance Market mainly as investment decision analysis tool.

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