Insights into the Drivers and Spatiotemporal Trends of Extreme Mediterranean Wildfires with Statistical Deep Learning. Artificial Intelligence for the Earth Systems, (2)4American Meteorological Society, October 2023. [PUMA: Deep Extreme Learning Mediterranean Spatiotemporal Statistical Trends Wildfires] URL
Insights into the Drivers and Spatiotemporal Trends of Extreme Mediterranean Wildfires with Statistical Deep Learning. Artificial Intelligence for the Earth Systems, (2)4American Meteorological Society, October 2023. [PUMA: Extreme Mediterranean Learning Wildfires Spatiotemporal Trends Statistical Deep from:scadsfct] URL
Leptin deficiency-caused behavioral change - A comparative analysis using EthoVision and DeepLabCut. Frontiers in neuroscience, (17)Frontiers Media S.A., Mar 24, 2023. [PUMA: topic_lifescience Behavioral Deep DeepLabCut, EthoVision, FIS_scads Obesity analysis, learning,]
SetQuence & SetOmic: Deep Set Transformer-based Representations of Cancer Multi-Omics. 2022 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2022, 139--147, IEEE, New York u. a., United States of America, 2022. [PUMA: topic_federatedlearn livinglab Deep FIS_scads Network, Neural Representations Set analysis, expression, gene genome, language molecular multi-omics, mutome, natural processing, sequence]
Two-step dynamic obstacle avoidance. Knowledge-based systems, (302)Elsevier Science B.V., Oct 25, 2024. [PUMA: topic_engineering Deep Dynamic FIS_scads Local Supervised avoidance, learning learning, obstacle path planning, reinforcement]
Spatial–temporal recurrent reinforcement learning for autonomous ships. Neural Networks, (2023)165:634--653, Elsevier Science B.V., Jun 15, 2023. [PUMA: topic_engineering Algorithms, Autonomous COLREG, Computer, Deep FIS_scads Networks, Neural Psychology, Recurrency, Reinforcement, Reward Ships, learning, reinforcement surface vehicle,]
Robust path following on rivers using bootstrapped reinforcement learning. Ocean engineering, (298)Elsevier Science B.V., Apr 15, 2024. [PUMA: topic_engineering Autonomous Deep FIS_scads Path Restricted following, learning, reinforcement surface vessel, waterways]
Deep reinforcement learning with artificial microswimmers. Emerging Topics in Artificial Intelligence (ETAI) 2022, (12204):104--110, 2022. [PUMA: topic_physchemistry Deep artificial learning microswimmers reinforcement]
Self-organized free-flight arrival for urban air mobility. Transportation Research Part C: Emerging Technologies, (167):104806, 2024. [PUMA: topic_engineering Deep Urban air eVTOL learning mobility reinforcement] URL
Neural network-assisted humanisation of COVID-19 hamster transcriptomic data reveals matching severity states in human disease. eBioMedicine, (108):105312, 2024. [PUMA: topic_mathfoundation COVID-19, Cross-species Deep Disease Hamster RNA-seq, Single-cell analysis, learning matching, model, state] URL
Towards the interpretability of deep learning models for multi-modal neuroimaging: Finding structural changes of the ageing brain. NeuroImage, (261):119504, 2022. [PUMA: topic_neuroinspired topic_lifescience Ageing, Brain-age, Cardiovascular Explainable Structural a.i., deep factors, learning mri, risk] URL
Artificial intelligence predicts immune and inflammatory gene signatures directly from hepatocellular carcinoma histology. J. Hepatol., (77)1:116--127, Elsevier BV, July 2022. [PUMA: topic_lifescience artificial deep gene image immune intelligence; learning; pathology; signatures; slide whole]
Uncertainty estimation in medical image classification: Systematic review. JMIR Med. Inform., (10)8:e36427, August 2022. [PUMA: topic_lifescience calibration; classification; deep detection; estimation image imaging; learning; medical network out-of-distribution 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: topic_lifescience Artificial Computational Convolutional Learning; Multiple-Instance Vision Weakly-supervised deep intelligence; learning networks; neural pathology; transformers;]
Weakly supervised annotation-free cancer detection and prediction of genotype in routine histopathology. J. Pathol., (256)1:50--60, Wiley, January 2022. [PUMA: topic_lifescience Lynch artificial cancer; colorectal computational deep digital instability intelligence; learning; microsatellite pathology; syndrome;]
Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer. J. Pathol., (256)3:269--281, Wiley, March 2022. [PUMA: topic_lifescience AI; LNM adipose and artificial biomarker; bowel cancer; colorectal deep digital early inflamed intelligence; learning; metastasis; new pT1 pT2 pathology; prediction predictive tissue;]
Model soups improve performance of dermoscopic skin cancer classifiers. Eur. J. Cancer, (173):307--316, Elsevier BV, September 2022. [PUMA: topic_lifescience Artificial Calibration; Deep Dermatology; Ensembles; Generalisation; Melanoma; Model Nevus; Robustness intelligence; learning; soups;]
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, March 2022. [PUMA: topic_lifescience Artificial Bladder Deep FGFR3 Molecular cancer; factor fibroblast for growth intelligence; learning; mutations; receptor testing therapy]
Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction. JHEP Rep., (4)4:100443, Elsevier BV, April 2022. [PUMA: topic_lifescience AI, Artificial CNN, Communications DICOM, Diagnosis; Digital HCC, Imaging Individual ML, MVI, Medicine; NAFLD, NASH, Prognosis Reporting TACE, TRIPOD, Transparent WSIs, a and artificial carcinoma; chemoembolisation; convolutional data deep diagnostic disease; fatty for hepatocellular images; imaging; in integration intelligence; invasion; learning; liver machine microvascular model multimodal multivariable network; neural non-alcoholic of or prediction slide steatohepatitis; support system; transarterial whole]
Introduction to the BioChemical Library (BCL): An application-based open-source toolkit for integrated cheminformatics and machine learning in computer-aided drug discovery. Front. Pharmacol., (13):833099, Frontiers Media SA, February 2022. [PUMA: topic_lifescience BCL; QSAR; biochemical cheminformatics; deep design; discovery; drug library; network; neural open-source]
Automatic lung segmentation and quantification of aeration in computed tomography of the chest using 3D transfer learning. Front. Physiol., (12):725865, 2021. [PUMA: ARDS; COVID-19; Jaccard deep index; learning; lung recruitment; segmentation; transfer uNet]
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]
Deep learning improves pancreatic cancer diagnosis using RNA-based variants. Cancers (Basel), (13)11:2654, MDPI AG, May 2021. [PUMA: association cancer; chronic deep learning; pancreatic pancreatitis; study topic_lifescience transcriptome-wide]
Predicting mutational status of driver and suppressor genes directly from histopathology with Deep Learning: A systematic study across 23 solid tumor types. Front. Genet., (12):806386, 2021. [PUMA: (AI); TCGA; artificail cancer deep genes; genetic intelligence learning; pathway pathway;]
SpheroScan: a user-friendly deep learning tool for spheroid image analysis. Gigascience, (12)Oxford University Press (OUP), December 2022. [PUMA: topic_federatedlearn 3D Image Mask R-CNN; analysis; deep high-throughput image learning; screening; segmentation spheroids;]