Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction. JHEP Rep., (4)4:100443, Elsevier BV, April 2022. [PUMA: 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]
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]
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: AI; LNM adipose and artificial biomarker; bowel cancer; colorectal deep digital early inflamed intelligence; learning; metastasis; new pT1 pT2 pathology; prediction predictive tissue;]
Sparse pseudocontact shift NMR data obtained from a non-canonical amino acid-linked lanthanide tag improves integral membrane protein structure prediction. J. Biomol. NMR, (77)3:69--82, June 2023. [PUMA: (IMPs); (PCSs); (ncAAs); Click Integral Non-canonical Pseudocontact Rosetta; Structure acids amino chemistry; membrane prediction proteins shifts topic_lifescience]
Benchmarking AlphaFold2 on peptide structure prediction. Structure, (31)1:111--119.e2, Elsevier BV, January 2023. [PUMA: AlphaFold2; benchmark; bonds; disulfide folding; pLDDT; peptides; prediction protein structure topic_lifescience]
Stroke-GFCN: ischemic stroke lesion prediction with a fully convolutional graph network. J. Med. Imaging (Bellingham), (10)4:044502, SPIE-Intl Soc Optical Eng, July 2023. [PUMA: graph imaging; learning; machine medical multi-modal networks; neural prediction stroke]
Biasing AlphaFold2 to predict GPCRs and kinases with user-defined functional or structural properties. Front. Mol. Biosci., (10):1121962, February 2023. [PUMA: (G-protein-coupled AlphaFold; GPCRs function; kinases; prediction protein receptors); structure topic_lifescience]