Adaptive weighting of Bayesian physics informed neural networks for multitask and multiscale forward and inverse problems. Journal of computational physics, (491)Academic Press Inc., 15.10.2023. [PUMA: FIS_scads training, Uncertainty Artificial Bayesian Quantification neural weight Multi-objective Monte physics-informed Intelligence, learning, Carlo, networks, Adaptive topic_lifescience Hamiltonian]
Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction. JHEP Rep., (4)4:100443, Elsevier BV, April 2022. [PUMA: a disease; HCC, or intelligence; liver multivariable non-alcoholic multimodal ML, artificial WSIs, images; prediction support integration TACE, DICOM, AI, network; deep neural Digital Diagnosis; MVI, transarterial fatty topic_lifescience microvascular convolutional in learning; imaging; Communications invasion; NAFLD, chemoembolisation; hepatocellular Reporting steatohepatitis; Transparent Individual slide machine Prognosis Artificial data for NASH, whole Medicine; TRIPOD, of CNN, and Imaging carcinoma; diagnostic system; model]
Artificial intelligence predicts immune and inflammatory gene signatures directly from hepatocellular carcinoma histology. J. Hepatol., (77)1:116--127, Elsevier BV, Juli 2022. [PUMA: image artificial immune intelligence; pathology; gene deep learning; signatures; slide topic_lifescience whole]
Artificial intelligence to identify genetic alterations in conventional histopathology. J. Pathol., (257)4:430--444, Wiley, Juli 2022. [PUMA: image artificial oncology intelligence; precision topic_lifescience analysis; biomarker;]
Artificial intelligence-based detection of FGFR3 mutational status directly from routine histology in bladder cancer: A possible preselection for molecular testing?. Eur. Urol. Focus, (8)2:472--479, Elsevier BV, März 2022. [PUMA: Artificial intelligence; learning; therapy for Deep mutations; Bladder cancer; Molecular fibroblast receptor testing topic_lifescience growth factor FGFR3]
Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology. Med. Image Anal., (79)102474:102474, Elsevier BV, Juli 2022. [PUMA: Convolutional Artificial intelligence; Multiple-Instance deep neural networks; learning Weakly-supervised Learning; transformers; pathology; topic_lifescience Vision Computational]
Brief Summary of Existing Research on Students’ Conceptions of AI. 1--2, Oktober 2022. [PUMA: FIS_scads models, education, mental preconceptions artificial ideas, beliefs, intelligence, k-12 learning, machine conceptions, area_responsibleai]
Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer. J. Pathol., (256)3:269--281, Wiley, März 2022. [PUMA: metastasis; inflamed intelligence; deep learning; bowel predictive LNM adipose pT2 pT1 digital biomarker; cancer; artificial AI; pathology; colorectal and topic_lifescience prediction new tissue; early]
Deep reinforcement learning with artificial microswimmers. Emerging Topics in Artificial Intelligence (ETAI) 2022, (12204):104--110, 2022. [PUMA: microswimmers artificial learning topic_physchemistry reinforcement Deep]
Democratising Artificial Intelligence for Pandemic Preparedness and Global Governance in Latin American and Caribbean Countries. arXiv, 2024. [PUMA: sciences Artificial Intelligence and FOS Computer Zno information] URL
Explainable artificial intelligence in skin cancer recognition: A systematic review. Eur. J. Cancer, (167):54--69, Elsevier BV, Mai 2022. [PUMA: Systematic Artificial Dermatology; intelligence; topic_lifescience Man-machine review Skin neoplasms; systems;]
How Does Explainability Look in Hybrid User Interfaces?. 251--256, 16.10.2023. [PUMA: FIS_scads artificial intelligence, hybrid reality mixed explainable user topic_visualcomputing interfaces,] URL
Identifying Secondary School Students' Misconceptions about Machine Learning: An Interview Study. WiPSCE '24: Proceedings of the 19th WiPSCE Conference on Primary and Secondary Computing Education Research, 1--10, Association for Computing Machinery, 16.09.2024. [PUMA: FIS_scads models, students mental misconceptions, artificial research, intelligence, qualitative study, learning, machine interview area_responsibleai conceptions]
Logics in Artificial Intelligence: 18th European Conference, JELIA 2023, Dresden, Germany, September 20--22, 2023, Proceedings. In Sarah Gaggl, Maria Vanina Martinez, und Magdalena Ortiz (Hrsg.), Lecture notes in computer science, Springer Nature Switzerland, Cham, 2023. [PUMA: Artificial in Intelligence AI Logics]
Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligence. NPJ Digit. Med., (7)1:76, März 2024. [PUMA: leukemia synthetic artificial clinical myeloid trials ai Yaff intelligence generative]
Model soups improve performance of dermoscopic skin cancer classifiers. Eur. J. Cancer, (173):307--316, Elsevier BV, September 2022. [PUMA: Artificial intelligence; learning; Deep Melanoma; soups; Dermatology; Robustness Calibration; Ensembles; topic_lifescience Model Generalisation; Nevus;]
NFDI4DS Transfer and Application. Gesellschaft für Informatik e.V., 2023. [PUMA: Infrastructures Artificial Intelligence NFDI Data Research Zno NFDI4DS Science] URL
Secondary school students' mental models and attitudes regarding artificial intelligence - A scoping review. Computers and education: artificial intelligence, (5)5:1--13, Elsevier Science B.V., Januar 2023. [PUMA: FIS_scads K-12 Mental models, Attitudes, education, Artificial Conceptions, intelligence, Scoping review area_responsibleai]
SetQuence & SetOmic: Deep set transformers for whole genome and exome tumour analysis. BioSystems, (235)Elsevier, Januar 2024. [PUMA: FIS_scads Humans, topic_federatedlearn Intelligence, Artificial Oncology, Research, livinglab Exome/genetics, Medical Neoplasms/genetics Biomedical]
The future of artificial intelligence in digital pathology - results of a survey across stakeholder groups. Histopathology, (80)7:1121--1127, Wiley, Juni 2022. [PUMA: artificial intelligence; pathology; topic_lifescience survey digital]