Feature Papers in Medical Statistics and Data Science Section

Recent years have witnessed an increase in the use of advanced data analysis methods in biomedical, clinical, and epidemiological research. The aim of this reprint is to highlight the practical aspects of new data analysis methods and to provide insights into the challenges in biostatistics and data...

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Format:	Buch
Sprache:	eng
Schlagworte:	ACE2 algorithmic fairness alpha and theta EEG band ratios AlphaFold2 artificial intelligence automated detection automated meta-analysis automation big data bioinformatic analysis Camelyon17 cancer carotid intima-media thickness childhood chronic kidney disease clinical outcome assessment clinical trials colon adenocarcinoma CpG DNA craniovertebral angle data imputation data missingness data preprocessing data presentation data science deep learning diabetes digital medicine DOPE electronic health records event detection gene expression genomic factors genomics hyperbaric oxygen therapy Kaplan–Meier estimator laboratory diagnostics logrank test machine learning medical diagnostics Medicine and Nursing Medicine: general issues membrane bilayer mental workload meta-analysis metagenomics MMP3 and TESC model explainability Modeller nephrology neuronal network Openpose ordinal variables outcomes outlier removal overweight Parkinson’s disease patches personalized medicine prediction models primary prevention protein structures Public health and preventive medicine RCT recurrent neural networks requirements engineering research synthesis RGB SARS-CoV-2 vaccines Shapley-based feature selection single-cell RNA-seq spike protein standardized regression coefficient statistical feature selection statistics structural models thema EDItEUR tragus treatment tumour type 1 diabetes weighted trajectory analysis WSI
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Beschreibung
Zusammenfassung:	Recent years have witnessed an increase in the use of advanced data analysis methods in biomedical, clinical, and epidemiological research. The aim of this reprint is to highlight the practical aspects of new data analysis methods and to provide insights into the challenges in biostatistics and data science. By considering recent developments in medical technology, the reprint includes novel approaches in the field of medical statistics and data science, covering meta-analysis, the assessment of clinical outcomes, machine learning, medical diagnostics, and genomic factors.
DOI:	10.3390/books978-3-7258-1044-4