標(biāo)題: Titlebook: Artificial Intelligence and Machine Learning in Healthcare; Ankur Saxena,Shivani Chandra Book 2021 The Editor(s) (if applicable) and The A [打印本頁] 作者: odometer 時(shí)間: 2025-3-21 19:19
書目名稱Artificial Intelligence and Machine Learning in Healthcare影響因子(影響力)
書目名稱Artificial Intelligence and Machine Learning in Healthcare影響因子(影響力)學(xué)科排名
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書目名稱Artificial Intelligence and Machine Learning in Healthcare網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Artificial Intelligence and Machine Learning in Healthcare被引頻次
書目名稱Artificial Intelligence and Machine Learning in Healthcare被引頻次學(xué)科排名
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書目名稱Artificial Intelligence and Machine Learning in Healthcare讀者反饋
書目名稱Artificial Intelligence and Machine Learning in Healthcare讀者反饋學(xué)科排名
作者: addition 時(shí)間: 2025-3-22 00:18
Artificial Intelligence in Personalized Medicine,garded in practicing an effective personalized medicine. Though machine learning is in the scenario of precision medicine first followed by personalized medicine, it still has to be accepted in the society for better development. This chapter gives an insight into how and where the artificial intelligence is used in the personalized medicine.作者: Microaneurysm 時(shí)間: 2025-3-22 01:55
Book 2021science, life science, and statistics incorporated into statistical models using existing data, discovering patterns in data to extract the information, and predicting the changes and diseases based on this data and models. The initial chapters of the book cover the practical applications of artific作者: Jubilation 時(shí)間: 2025-3-22 05:19
https://doi.org/10.1007/978-3-540-75276-9rous missing values, errors, and biased inputs. This is due to under- or over-representation of certain groups of data, trivial data curation methods, etc. In this chapter, we describe Perceptive Bias, Processing Bias, and the ways to compute bias for Medical Big Data analysis.作者: Odyssey 時(shí)間: 2025-3-22 12:26
Standards and Protocols for Interoperability map simulation of COVID-19’s international expansion to date and estimate virus distribution throughout all regions and countries. Detailed overview of both region-wise and state-wise recorded events; forecast of a viral pandemic attack, deaths, and recovered cases; and the degree to which it is spreading globally are included in this chapter.作者: Sinus-Node 時(shí)間: 2025-3-22 14:54
Visualization and Prediction of COVID-19 Using AI and ML, map simulation of COVID-19’s international expansion to date and estimate virus distribution throughout all regions and countries. Detailed overview of both region-wise and state-wise recorded events; forecast of a viral pandemic attack, deaths, and recovered cases; and the degree to which it is spreading globally are included in this chapter.作者: DEMUR 時(shí)間: 2025-3-22 19:00 作者: 繁殖 時(shí)間: 2025-3-23 00:59
Bias in Medical Big Data and Machine Learning Algorithms,rous missing values, errors, and biased inputs. This is due to under- or over-representation of certain groups of data, trivial data curation methods, etc. In this chapter, we describe Perceptive Bias, Processing Bias, and the ways to compute bias for Medical Big Data analysis.作者: prediabetes 時(shí)間: 2025-3-23 05:14 作者: 芳香一點(diǎn) 時(shí)間: 2025-3-23 08:04 作者: 嗎啡 時(shí)間: 2025-3-23 12:45
Artificial Intelligence in Personalized Medicine,cannot maintain the modest outlay of the personalized medicine-centered treatment. Somehow, the accuracy of the medication and diagnosis using personalized medicine is lower when manualized than when involving artificial intelligence. Machine learning is one of the mostly used artificial intelligenc作者: G-spot 時(shí)間: 2025-3-23 14:01 作者: 自愛 時(shí)間: 2025-3-23 19:55
Transfer Learning in Biological and Health Care,tional machine learning makes a basic assumption that the distribution of training data and testing data should be the same. But in numerous real-world cases, this identical-distribution assumption of training data and testing data does not hold at all. For example, suppose if we have a model to rec作者: 公共汽車 時(shí)間: 2025-3-23 23:00
Visualization and Prediction of COVID-19 Using AI and ML,, such as the horticultural zone, the agricultural zone, the economic zone, the public transport market, and so on. We published an analysis that identified the effects of the global pandemic using next-generation technologies to see how COVID-19 affected the globe. Prediction is a standard exercise作者: FELON 時(shí)間: 2025-3-24 06:21 作者: Rct393 時(shí)間: 2025-3-24 07:26 作者: Criteria 時(shí)間: 2025-3-24 11:27 作者: 確定方向 時(shí)間: 2025-3-24 18:01
Bias in Medical Big Data and Machine Learning Algorithms,esults from several findings show that these algorithms have potential to gain negative impact on healthcare system as compared to the existing primitive healthcare systems which involve physicians. Current algorithms are accused of these deficiencies resulting from biased training data bearing nume作者: 混合物 時(shí)間: 2025-3-24 23:04 作者: Carcinogen 時(shí)間: 2025-3-25 01:38 作者: 疾馳 時(shí)間: 2025-3-25 06:02
e-Society and the Social Divide will help the readers to understand that this emerging information technology is becoming society’s most progressive tool and further may effectively use the information for their research endeavours.作者: Defense 時(shí)間: 2025-3-25 07:53
Content, Communication and Tools, that can be applied for patient stratification based on probable disease risk, prognosis, and/or response to treatment. The advanced computational expertise using artificial intelligence for biological data analysis is also being used to speed up the drug discovery process of precision medicine. I作者: Prognosis 時(shí)間: 2025-3-25 15:32
Smart Labels, Smart Tags and RFIDld domain can be costly for any organization, and it is also inappropriate to throw away the newly obtained data just because it is from another domain..In this chapter, we retrained various state-of-the-arts convolutional deep learning models using transfer learning by supplying the data related to作者: DEBT 時(shí)間: 2025-3-25 18:03 作者: condescend 時(shí)間: 2025-3-25 22:22
Customer Relationship Management these techniques in modeling the progression of the tumor along with its effective treatment. Although the different ML algorithms have provided an improved understanding of the tumor condition, a proper validation is required for their applications in everyday clinical practices. Keeping in mind t作者: Obscure 時(shí)間: 2025-3-26 00:30 作者: 參考書目 時(shí)間: 2025-3-26 06:14 作者: 錫箔紙 時(shí)間: 2025-3-26 09:50 作者: Parameter 時(shí)間: 2025-3-26 16:01
Artificial Intelligence and Machine Learning in Healthcare作者: 把…比做 時(shí)間: 2025-3-26 17:13
Artificial Intelligence and Machine Learning in Healthcare978-981-16-0811-7作者: 高興去去 時(shí)間: 2025-3-26 23:39
Practical Applications of Artificial Intelligence for Disease Prognosis and Management,of artificial intelligence techniques to medical data management. These techniques can analyse different types of data retrieved from patient samples, such as structured images, features based on patient vitals for predicting the probability of the outcome of a disease and design a better treatment 作者: EWER 時(shí)間: 2025-3-27 03:36
Automated Diagnosis of Diabetes Mellitus Based on Machine Learning, will help the readers to understand that this emerging information technology is becoming society’s most progressive tool and further may effectively use the information for their research endeavours.作者: 填料 時(shí)間: 2025-3-27 06:29
Artificial Intelligence in Precision Medicine: A Perspective in Biomarker and Drug Discovery,, that can be applied for patient stratification based on probable disease risk, prognosis, and/or response to treatment. The advanced computational expertise using artificial intelligence for biological data analysis is also being used to speed up the drug discovery process of precision medicine. I作者: 破譯 時(shí)間: 2025-3-27 12:35 作者: 殘酷的地方 時(shí)間: 2025-3-27 15:30
Machine Learning Approaches in Detection and Diagnosis of COVID-19,elligence are well-established methods in image analysis, making them suitable for the analysis of computerized tomography (CT) chest scans and X-ray images. This provides a novel class of testing that is noninvasive and can help in point-of-care testing by the use of portable CXR machines. AI-based作者: Optimum 時(shí)間: 2025-3-27 18:04
Applications of Machine Learning Algorithms in Cancer Diagnosis, these techniques in modeling the progression of the tumor along with its effective treatment. Although the different ML algorithms have provided an improved understanding of the tumor condition, a proper validation is required for their applications in everyday clinical practices. Keeping in mind t作者: phlegm 時(shí)間: 2025-3-27 23:58 作者: 控訴 時(shí)間: 2025-3-28 06:10 作者: BAIT 時(shí)間: 2025-3-28 07:54
978-981-16-0813-1The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor作者: 宣稱 時(shí)間: 2025-3-28 10:39
Ankur Saxena,Shivani ChandraAnalyzes the applications of artificial intelligence and machine learning in healthcare.Discusses the role of artificial intelligence in disease prognosis and management.Explores the role of AI in per作者: 乞丐 時(shí)間: 2025-3-28 17:33 作者: 拖債 時(shí)間: 2025-3-28 21:40 作者: 圓木可阻礙 時(shí)間: 2025-3-29 02:59 作者: 開頭 時(shí)間: 2025-3-29 03:54
e-Society and the Social Dividecannot maintain the modest outlay of the personalized medicine-centered treatment. Somehow, the accuracy of the medication and diagnosis using personalized medicine is lower when manualized than when involving artificial intelligence. Machine learning is one of the mostly used artificial intelligenc作者: 增減字母法 時(shí)間: 2025-3-29 09:38
Content, Communication and Toolsedical data and the gained knowledge. The uniqueness of this concept is implied by “precision medicine,” which amalgamates contemporary computational methodologies such as artificial intelligence and big data analytics for achieving an informed decision, considering variability in patient’s clinical作者: 業(yè)余愛好者 時(shí)間: 2025-3-29 12:59 作者: Misgiving 時(shí)間: 2025-3-29 16:23
