scholarly journals The Role of Artificial Intelligence in the Diagnosis and Prognosis of Renal Cell Tumors

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 206
Author(s):  
Matteo Giulietti ◽  
Monia Cecati ◽  
Berina Sabanovic ◽  
Andrea Scirè ◽  
Alessia Cimadamore ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Renal Cancer ◽  
Renal Cell ◽  
Treatment Plan ◽  
Molecular Data ◽  
Receiver Operating Curve ◽  
Diagnosis And Prognosis ◽  
Study Results ◽  
Gene Panels ◽  
Next Generation Sequencing Ngs

The increasing availability of molecular data provided by next-generation sequencing (NGS) techniques is allowing improvement in the possibilities of diagnosis and prognosis in renal cancer. Reliable and accurate predictors based on selected gene panels are urgently needed for better stratification of renal cell carcinoma (RCC) patients in order to define a personalized treatment plan. Artificial intelligence (AI) algorithms are currently in development for this purpose. Here, we reviewed studies that developed predictors based on AI algorithms for diagnosis and prognosis in renal cancer and we compared them with non-AI-based predictors. Comparing study results, it emerges that the AI prediction performance is good and slightly better than non-AI-based ones. However, there have been only minor improvements in AI predictors in terms of accuracy and the area under the receiver operating curve (AUC) over the last decade and the number of genes used had little influence on these indices. Furthermore, we highlight that different studies having the same goal obtain similar performance despite the fact they use different discriminating genes. This is surprising because genes related to the diagnosis or prognosis are expected to be tumor-specific and independent of selection methods and algorithms. The performance of these predictors will be better with the improvement in the learning methods, as the number of cases increases and by using different types of input data (e.g., non-coding RNAs, proteomic and metabolic). This will allow for more precise identification, classification and staging of cancerous lesions which will be less affected by interpathologist variability.

scholarly journals Molecular-based precision oncology clinical decision making augmented by artificial intelligence

2021 ◽  
Author(s):  
Jia Zeng ◽  
Md Abu Shufean
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Molecular Data ◽  
Molecular Testing ◽  
Precision Oncology ◽  
Current Application ◽  
Next Generation Sequencing Ngs ◽  
Molecular Sequencing

The rapid growth and decreasing cost of Next-generation sequencing (NGS) technologies have made it possible to conduct routine large panel genomic sequencing in many disease settings, especially in the oncology domain. Furthermore, it is now known that optimal disease management of patients depends on individualized cancer treatment guided by comprehensive molecular testing. However, translating results from molecular sequencing reports into actionable clinical insights remains a challenge to most clinicians. In this review, we discuss about some representative systems that leverage artificial intelligence (AI) to facilitate some processes of clinicians’ decision making based upon molecular data, focusing on their application in precision oncology. Some limitations and pitfalls of the current application of AI in clinical decision making are also discussed.

scholarly journals Characteristics and Clinical Application of Extracellular Vesicle-Derived DNA

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3827
Author(s):  
Jae Young Hur ◽  
Kye Young Lee
Keyword(s):  
Therapeutic Potential ◽  
Extracellular Vesicle ◽  
Clinical Settings ◽  
Biomarker Detection ◽  
Diagnosis And Prognosis ◽  
Double Stranded Dna ◽  
Fundamental Research ◽  
The Stability ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

Extracellular vesicles (EVs) carry RNA, proteins, lipids, and diverse biomolecules for intercellular communication. Recent studies have reported that EVs contain double-stranded DNA (dsDNA) and oncogenic mutant DNA. The advantage of EV-derived DNA (EV DNA) over cell-free DNA (cfDNA) is the stability achieved through the encapsulation in the lipid bilayer of EVs, which protects EV DNA from degradation by external factors. The existence of DNA and its stability make EVs a useful source of biomarkers. However, fundamental research on EV DNA remains limited, and many aspects of EV DNA are poorly understood. This review examines the known characteristics of EV DNA, biogenesis of DNA-containing EVs, methylation, and next-generation sequencing (NGS) analysis using EV DNA for biomarker detection. On the basis of this knowledge, this review explores how EV DNA can be incorporated into diagnosis and prognosis in clinical settings, as well as gene transfer of EV DNA and its therapeutic potential.

Effect of host immunity on metastatic potential in renal cell carcinoma: the assessment of optimal in vivo models to study metastatic behavior of renal cancer cells

Tumor Biology ◽  
2012 ◽  
Vol 33 (2) ◽  
pp. 551-559 ◽  
Author(s):  
Minoru Kobayashi ◽  
Tatsuo Morita ◽  
Nicole A. L. Chun ◽  
Aya Matsui ◽  
Masafumi Takahashi ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Cancer Cells ◽  
Renal Cancer ◽  
Renal Cell ◽  
Metastatic Potential ◽  
Host Immunity ◽  
In Vivo Models ◽  
Metastatic Behavior

scholarly journals The Combined Effects of Sports Smart Bracelet and Multi-Component Exercise Program on Exercise Motivation among the Elderly in Macau

Medicina ◽  
2021 ◽  
Vol 57 (1) ◽  
pp. 34
Author(s):  
Cheuk Kei Lao ◽  
Bing Long Wang ◽  
Richard S. Wang ◽  
Hsiao Yun Chang
Keyword(s):  
Artificial Intelligence ◽  
Exercise Training ◽  
Training Programs ◽  
Exercise Program ◽  
The Elderly ◽  
Control Group ◽  
Exercise Motivation ◽  
Sport Training ◽  
Study Results ◽  
Significant Difference

Background and objectives: Faced with the serious problem of an aging population, exercise is one of the most effective ways to maintain the health of the elderly. In recent years, with the popularization of smartphones, the elderly have increasingly accepted technological products that incorporate artificial intelligence (AI). However, there is not much research on using artificial intelligence bracelets to enhance elders’ motivation and participation in exercise. Therefore, the purpose of this study is to evaluate the effectiveness of the combination of sports smart bracelets and multi-sport training programs on the motivation of the elderly in Macau. Materials and Methods: The study was conducted with a randomized trial design in a 12 week multi-sport exercise training intervention. According to the evaluation, a total of sixty elders’ pre- and post-test data were included in this study. Results: After 12 weeks of multi-sport exercise training, the evaluation scores on the exercise motivation scale (EMS) increased significantly in the group wearing exercise bracelets and those taking part in the multi-component exercise program, and the degree of progress reached a statistically significant level, but the control group did not show any statistically significant difference. The influence of the combination of sports smart bracelets and multi-sport training programs on elders’ motivation is clearer. Conclusions: The use of sports smart bracelets by elderly people in conjunction with diverse exercise training can effectively enhance elders’ motivation and increase their participation in regular exercise. The combination of sports smart bracelets and multi-sport training programs is worth promoting in the elderly population.

scholarly journals Misconceptions in the health technology industry that are delaying the translation of artificial intelligence technology into relevant clinical applications

2021 ◽  
Vol 54 (4) ◽  
pp. 243-245
Author(s):  
Fabíola Macruz
Keyword(s):  
Artificial Intelligence ◽  
Human Performance ◽  
Health Technology ◽  
Medical Community ◽  
Technology Industry ◽  
Diagnosis And Prognosis ◽  
Starting Point ◽  
Causative Factors ◽  
The Status ◽  
Artificial Intelligence Technology

Abstract There is great optimism that artificial intelligence (AI), as it disrupts the medical world, will provide considerable improvements in all areas of health care, from diagnosis to treatment. In addition, there is considerable evidence that AI algorithms have surpassed human performance in various tasks, such as analyzing medical images, as well as correlating symptoms and biomarkers with the diagnosis and prognosis of diseases. However, the mismatch between the performance of AI-based software and its clinical usefulness is still a major obstacle to its widespread acceptance and use by the medical community. In this article, three fundamental concepts observed in the health technology industry are highlighted as possible causative factors for this gap and might serve as a starting point for further evaluation of the structure of AI companies and of the status quo.

scholarly journals Identification of a Novel Stem Cell Subtype for Clear Cell Renal Cell Carcinoma Based on Stem Cell Gene Profiling

2021 ◽  
Vol 11 ◽  
Author(s):  
Hongzhi Wang ◽  
Hanjiang Xu ◽  
Quan Cheng ◽  
Chaozhao Liang
Keyword(s):  
Renal Cell Carcinoma ◽  
Stem Cell ◽  
Cancer Stem Cell ◽  
Renal Cancer ◽  
Renal Cell ◽  
Clear Cell ◽  
Cell Renal Cell Carcinoma ◽  
Gene Sets ◽  
Cell Gene ◽  
Stem Cell Gene

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer and is characterized by high rates of metastasis. Cancer stem cell is a vital cause of renal cancer metastasis and recurrence. However, little is known regarding the change and the roles of stem cells during the development of renal cancer. To clarify this problem, we developed a novel stem cell clustering strategy. Based on The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) genomic datasets, we used 19 stem cell gene sets to classify each dataset. A machine learning method was used to perform the classification. We classified ccRCC into three subtypes—stem cell activated (SC-A), stem cell dormant (SC-D), and stem cell excluded (SC-E)—based on the expressions of stem cell-related genes. Compared with the other subtypes, C2(SC-A) had the highest degree of cancer stem cell concentration, the highest level of immune cell infiltration, a distinct mutation landscape, and the worst prognosis. Moreover, drug sensitivity analysis revealed that subgroup C2(SC-A) had the highest sensitivity to immunotherapy CTLA-4 blockade and the vascular endothelial growth factor receptor (VEGFR) inhibitor sunitinib. The identification of ccRCC subtypes based on cancer stem cell gene sets demonstrated the heterogeneity of ccRCC and provided a new strategy for its treatment.

scholarly journals Chatbots by business vis-à-vis consumers: A new form of power and information asymmetry

2021 ◽  
Vol 129 ◽  
pp. 05002
Author(s):  
Zanda Davida
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Information Asymmetry ◽  
Value Added ◽  
Legal Framework ◽  
Consumer Law ◽  
Study Results ◽  
The Sixties ◽  
Guidance Documents ◽  
New Form

Research background: The first notable early chatbots were created in the sixties, but the growing use of artificial intelligence (AI) has powered them significantly. Studies show that basically chatbots are created and used for purposes by government and business, mostly in consumer service and marketing. The new Proposal of the Artificial intelligence act aims to promote the uptake of AI and address the risks associated with certain uses of such technology. However, the act contains only minimum transparency obligation for some specific AL systems such as chatbots. Purpose of the article: In light of this issue, the article aims to discuss how existing European Union (EU) consumer law is equipped to deal with situations in which the use of chatbots can pose the risks of manipulation, aggressive commercial practices, intrusion into privacy, exploitation of a consumer’s vulnerabilities and algorithmic decision making based on biased or discriminatory results. Methods: The article will analyse the legal framework, compare guidance documents and countries’ experiences, study results of different consumer behavior researches and scientific articles. Findings & Value added: The article reveals several gaps in current EU consumer law and discusses the flaws of proposing legislation (particularly the Proposal for an Artificial intelligence act) regarding relations between business and consumers.

scholarly journals Research on the Application Mode of Green Environment Design under the Background of Artificial Intelligence

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Hui Liu ◽  
Guanghui Song ◽  
Linlin Yan
Keyword(s):  
Artificial Intelligence ◽  
Process Analysis ◽  
Current Status ◽  
Design System ◽  
Environment Design ◽  
Application Model ◽  
Study Results ◽  
Application Mode ◽  
Design Function ◽  
And Function

In the field of green environmental design, the design system of environmental art is a complex and multidimensional cross-domain fusion system, which can be regarded as a large task system. The development model that combines artificial intelligence (AI) technology and green environment design can not only integrate and analyze problems quickly and efficiently but also provide designers with new design ideas, gradually extending traditional environment design concepts, producing more diverse artistic creation methods, and shifting from a fixed application model to a more diversified artistic development. Therefore, on the basis of summarizing and analyzing previous research works, this paper expounded the research status and significance of green environment design, elaborated the development background, current status, and future challenges of AI technology, introduced the network topology and platform frame structures of green environment design under the AI background, constructed a technical framework of green environment design under the AI background, analyzed the methods and principles of program design and function development, proposed the application model of green environment design under the AI background, conducted design function model optimization and intelligent design process analysis, and finally discussed the evaluation indicators and hierarchical analysis of the green environment design under the AI background. The results show that the application mode of combining AI technology and green environment design can not only help designers break through traditional time and space barriers and use multidimensional thinking but also help designers have a new understanding of artistic design concept and give full play to the advantages of artificial intelligence in a green environment. The study results of this paper provide a reference for further research on the application mode of green environment design under the AI background.

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