Genetic regulation of PCSK9 (proprotein convertase subtilisin/Kexin type 9) plasma levels and its impact on atherosclerotic vascular disease phenotypes. Circ. Genom. Precis. Med., (11)5:e001992, Ovid Technologies (Wolters Kluwer Health), May 2018. [PUMA: association atherosclerosis; genome-wide study]
Optimization of the Mainzelliste software for fast privacy-preserving record linkage. J. Transl. Med., (19)1:33, Springer Science and Business Media LLC, January 2021. [PUMA: Blocking; Locality-sensitive Mainzelliste; Privacy-preserving hashing; linkage record]
Proteomics to improve phenotyping in obese patients with heart failure with preserved ejection fraction. Eur. J. Heart Fail., (23)10:1633--1644, Wiley, October 2021. [PUMA: Biomarker; Fibrosis; Heart Inflammation; Obesity; Proteomics ejection failure fraction; preserved topic_lifescience with]
Model soups improve performance of dermoscopic skin cancer classifiers. Eur. J. Cancer, (173):307--316, Elsevier BV, September 2022. [PUMA: Artificial Calibration; Deep Dermatology; Ensembles; Generalisation; Melanoma; Model Nevus; Robustness intelligence; learning; soups; topic_lifescience]
A multitask deep-learning method for predicting membrane associations and secondary structures of proteins. J. Proteome Res., (20)8:4089--4100, American Chemical Society (ACS), August 2021. [PUMA: convolutional deep learning; long memory multitask networks; neural prediction prediction; secondary short-term structure topic_lifescience topology transmembrane]
Automated algorithm selection on continuous black-box problems by combining Exploratory Landscape Analysis and machine learning. Evol. Comput., (27)1:99--127, MIT Press, 2019. [PUMA: Automated algorithm analysis; black-box continuous exploratory landscape learning; machine optimization. optimization; selection; single-objective]
Multi-source dataset of e-commerce products with attributes for property matching. Data Brief, (41)107884:107884, Elsevier BV, April 2022. [PUMA: Data Ontology; Property engineering; integration; matching]
Uncertainty estimation in medical image classification: Systematic review. JMIR Med. Inform., (10)8:e36427, August 2022. [PUMA: calibration; classification; deep detection; estimation image imaging; learning; medical network out-of-distribution topic_lifescience uncertainty]
Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology. Med. Image Anal., (79)102474:102474, Elsevier BV, July 2022. [PUMA: Artificial Computational Convolutional Learning; Multiple-Instance Vision Weakly-supervised deep intelligence; learning networks; neural pathology; transformers;]
Veratridine can bind to a site at the mouth of the channel pore at human cardiac sodium channel NaV1.5. Int. J. Mol. Sci., (23)4:2225, MDPI AG, February 2022. [PUMA: Rosetta; SCN5A; cardiac channels channels; docking; electrophysiology; molecular mutagenesis; site-directed sodium topic_lifescience toxins; veratridine; voltage-gated]
Memory-efficient deep learning on a SpiNNaker 2 prototype. Front. Neurosci., (12):840, Frontiers Media SA, November 2018. [PUMA: SpiNNaker; deep efficient energy footprint; hardware; memory parallelism; pruning; rewiring; sparsity]
Automated algorithm selection: Survey and perspectives. Evol. Comput., (27)1:3--45, MIT Press, 2019. [PUMA: Automated algorithm analysis; approaches; automated combinatorial configuration; continuous data exploratory feature-based landscape learning; machine metalearning optimisation; selection; streams.;]
Search dynamics on multimodal multiobjective problems. Evol. Comput., (27)4:577--609, MIT Press - Journals, 2019. [PUMA: Multiobjective analysis; ascent; gradient hypervolume landscape multimodality; optimization. optimization; set-based]
Relationship between fermented dairy consumption, circulating short-chain acylcarnitines and angiographic severity of coronary artery disease. Nutr. Metab. Cardiovasc. Dis., (30)10:1662--1672, Elsevier BV, September 2020. [PUMA: Acetylcarnitine; Coronary Fermented Metabolomics artery dairy disease; products;]
Common variants in the CLDN2-MORC4 and PRSS1-PRSS2 loci confer susceptibility to acute pancreatitis. Pancreatology, (18)5:477--481, Elsevier BV, July 2018. [PUMA: Acute Genetics; Risk Single factors; nucleotide pancreatitis; polymorphisms]
Artificial intelligence to identify genetic alterations in conventional histopathology. J. Pathol., (257)4:430--444, Wiley, July 2022. [PUMA: analysis; artificial biomarker; image intelligence; oncology precision]
Analysis of GPRC6A variants in different pancreatitis etiologies. Pancreatology, (20)7:1262--1267, Elsevier BV, October 2020. [PUMA: Calcium; G-Protein Genetics; Inflammation; Pancreatitis coupled receptor; topic_lifescience]
Explainable artificial intelligence in skin cancer recognition: A systematic review. Eur. J. Cancer, (167):54--69, Elsevier BV, May 2022. [PUMA: Artificial Dermatology; Man-machine Skin Systematic intelligence; neoplasms; review systems; topic_lifescience]
Classification of hyperspectral endocrine tissue images using support vector machines. Int. J. Med. Robot., (16)5:1--10, Wiley, October 2020. [PUMA: and assisted computer guided head imaged imaging; intraoperative neck; surgery; thyroidectomy]
Two for One: Querying Property Graph Databases Using SPARQL via Gremlinator. Proceedings of the 1st ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA), Association for Computing Machinery, New York, NY, USA, 2018. [PUMA: SPARQL, graph gremlin, gremlinator, property traversal,] URL