Clinical Studies, Big Data, and Artificial Intelligence in Nephrology and Transplantation
In recent years, artificial intelligence has increasingly been playing an essential role in diverse areas in medicine, assisting clinicians in patient management. In nephrology and transplantation, artificial intelligence can be utilized to enhance clinical care, such as through hemodialysis prescri...
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| Year of Publication: | 2021 |
| Language: | English |
| Physical Description: | 1 electronic resource (374 p.) |
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Cheungpasitporn, Wisit edt Clinical Studies, Big Data, and Artificial Intelligence in Nephrology and Transplantation Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 1 electronic resource (374 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier In recent years, artificial intelligence has increasingly been playing an essential role in diverse areas in medicine, assisting clinicians in patient management. In nephrology and transplantation, artificial intelligence can be utilized to enhance clinical care, such as through hemodialysis prescriptions and the follow-up of kidney transplant patients. Furthermore, there are rapidly expanding applications and validations of comprehensive, computerized medical records and related databases, including national registries, health insurance, and drug prescriptions. For this Special Issue, we made a call to action to stimulate researchers and clinicians to submit their invaluable works and present, here, a collection of articles covering original clinical research (single- or multi-center), database studies from registries, meta-analyses, and artificial intelligence research in nephrology including acute kidney injury, electrolytes and acid–base, chronic kidney disease, glomerular disease, dialysis, and transplantation that will provide additional knowledge and skills in the field of nephrology and transplantation toward improving patient outcomes. English Medicine bicssc tacrolimus C/D ratio tacrolimus metabolism everolimus conversion kidney transplantation gut microbiome renal transplant recipient diarrhea immunosuppressive medication gut microbiota 16S rRNA sequencing butyrate-producing bacteria Proteobacteria torquetenovirus immunosuppression transplantation immunosuppressed host outcome renal transplantation Goodpasture syndrome anti-GBM disease epidemiology hospitalization outcomes acute kidney injury risk prediction artificial intelligence patent ductus arteriosus conservative management blood pressure eradication interferon-free regimen hepatitis C infection kidney transplant allograft steatosis lipopeliosis transplant numbers live donors public awareness Google TrendsTM machine learning big data nephrology chronic kidney disease NLR PLR RPGN predictive value hemodialysis withdrawal cellular crescent global sclerosis procurement kidney biopsy glomerulosclerosis minimally-invasive donor nephrectomy robot-assisted surgery laparoscopic surgery organ donation living kidney donation MeltDose® LCPT renal function liver transplantation metabolism erythropoietin fibroblast growth factor 23 death weekend effect in-hospital mortality comorbidity dialysis elderly klotho α-Klotho FGF-23 kidney donor Nephrology CKD-MBD CKD-Mineral and Bone Disorder deceased donor Eurotransplant Senior Program risk stratification intensive care kidney transplant recipients long-term outcomes graft failure cardiovascular mortality lifestyle inflammation vascular calcification bone mineral density dual-energy X-ray absorptiometry living donation repeated kidney transplantation graft survival prolonged ischaemic time patient survival pre-emptive transplantation metabolomics urine acute rejection allograft cystatin C hyperfiltration kidney injury molecule (KIM)-1 tubular damage genetic polymorphisms (cardiac) surgery inflammatory cytokines clinical studies chronic kidney disease (CKD) no known kidney disease (NKD) ICD-10 billing codes phenotyping electronic health record (EHR) estimated glomerular filtration rate (eGFR) machine learning (ML) generalized linear model network (GLMnet) random forest (RF) artificial neural network (ANN), clinical natural language processing (clinical NLP) discharge summaries laboratory values area under the receiver operating characteristic (AUROC) area under the precision-recall curve (AUCPR) fibrosis extracellular matrix collagen type VI living-donor kidney transplantation ethnic disparity 3-0365-1134-2 3-0365-1135-0 Thongprayoon, Charat edt Kaewput, Wisit edt Cheungpasitporn, Wisit oth Thongprayoon, Charat oth Kaewput, Wisit oth |
| language |
English |
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eBook |
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Thongprayoon, Charat Kaewput, Wisit Cheungpasitporn, Wisit Thongprayoon, Charat Kaewput, Wisit |
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Thongprayoon, Charat Kaewput, Wisit Cheungpasitporn, Wisit Thongprayoon, Charat Kaewput, Wisit |
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HerausgeberIn HerausgeberIn Sonstige Sonstige Sonstige |
| title |
Clinical Studies, Big Data, and Artificial Intelligence in Nephrology and Transplantation |
| spellingShingle |
Clinical Studies, Big Data, and Artificial Intelligence in Nephrology and Transplantation |
| title_full |
Clinical Studies, Big Data, and Artificial Intelligence in Nephrology and Transplantation |
| title_fullStr |
Clinical Studies, Big Data, and Artificial Intelligence in Nephrology and Transplantation |
| title_full_unstemmed |
Clinical Studies, Big Data, and Artificial Intelligence in Nephrology and Transplantation |
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Clinical Studies, Big Data, and Artificial Intelligence in Nephrology and Transplantation |
| title_new |
Clinical Studies, Big Data, and Artificial Intelligence in Nephrology and Transplantation |
| title_sort |
clinical studies, big data, and artificial intelligence in nephrology and transplantation |
| publisher |
MDPI - Multidisciplinary Digital Publishing Institute |
| publishDate |
2021 |
| physical |
1 electronic resource (374 p.) |
| isbn |
3-0365-1134-2 3-0365-1135-0 |
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Not Illustrated |
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