Vai al contenuto principale della pagina

Clinical Studies, Big Data, and Artificial Intelligence in Nephrology and Transplantation



(Visualizza in formato marc)    (Visualizza in BIBFRAME)

Autore: Cheungpasitporn Wisit Visualizza persona
Titolo: Clinical Studies, Big Data, and Artificial Intelligence in Nephrology and Transplantation Visualizza cluster
Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica: 1 electronic resource (374 p.)
Soggetto topico: Medicine
Soggetto non controllato: 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
Persona (resp. second.): ThongprayoonCharat
KaewputWisit
CheungpasitpornWisit
Sommario/riassunto: 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.
Titolo autorizzato: Clinical Studies, Big Data, and Artificial Intelligence in Nephrology and Transplantation  Visualizza cluster
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910557367503321
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui