Psoriasis

Conditional Mutual Information Based Diffusion Posterior Sampling for Solving Inverse Problems

Inverse problems are prevalent across various disciplines in science and engineering. In the field of computer vision, tasks such as inpainting, deblurring, and super-resolution are commonly formulated as inverse problems. Recently, diffusion models (DMs) have emerged as a promising approach for addressing noisy linear inverse problems, offering effective solutions without requiring additional t...

Transformer-Driven Inverse Problem Transform for Fast Blind Hyperspectral Image Dehazing

Hyperspectral dehazing (HyDHZ) has become a crucial signal processing technology to facilitate the subsequent identification and classification tasks, as the airborne visible/infrared imaging spectrometer (AVIRIS) data portal reports a massive portion of haze-corrupted areas in typical hyperspectral remote sensing images. The idea of inverse problem transform (IPT) has been proposed in recent re...

Transcriptomic profiling and machine learning uncover gene signatures of psoriasis endotypes and disease severity

Despite increased understanding of psoriasis pathogenesis, molecular classification of clinical phenotypes and disease severity is poorly defined. Kno...

ProStab: Prediction of protein stability change upon mutations by protein language and inverse folding models

Predicting protein stability change upon mutation is critical for protein engineering, yet remains limited by the modeling assumptions of physics-base...

Benchmarking antigen-aware inverse folding methods for antibody design

Computational antibody design has seen many recent advances pioneered via the use of language models and advanced structure prediction tools. Developi...

MechanoAge, a machine learning platform to identify individuals susceptible to breast cancer based on mechanical properties of single cells

Existing breast cancer risk models inadequately identify individuals at latent risk, particularly among women without known genetic mutations or famil...

Predicting antifolate resistance in the unculturable fungal pathogen Pneumocystis jirovecii

Pneumocystis jirovecii is a fungal pathogen causing Pneumocystis pneumonia in humans, mainly in immunocompromised individuals. Infections by P. jirove...

Dietary Protein Source Shapes Gut Microbial Structure and Predicted Function: A Meta-Analysis with Machine Learning

Dietary proteins are major modulators of gut microbial ecology, yet the microbial signatures and functional consequences of plant-versus animal-based ...

Effects of the Neutral CB1 Receptor Antagonist AM6527 on Spontaneous, Consummatory, and Motivated Behavior in Mice

The cannabinoid type-1 receptor (CB1R) signaling pathway plays a central role in regulating motivational and feeding behaviors. Neutral CB1R antagonis...

A Generative Foundation Model for Antibody Design

Antibodies are indispensable components of the immune system, yet the design of high-affinity antibodies remains a time-consuming and experimentally i...

RNA sequence design and protein–DNA specificity prediction with NA-MPNN

RNA sequence design and protein–DNA binding specificity prediction can both be framed as nucleic acid inverse-folding problems: finding the most likel...

Targeted Enzymatic Fragmentation of Lipoprotein(a) via Kringle IV Domains: A Clearance-Enhancing Therapeutic Strategy for Cardiovascular Disease

Elevated lipoprotein(a) [Lp(a)] is an independent, genetically determined risk factor for atherosclerotic cardiovascular disease (ASCVD). Its unique a...

Finetuning Foundation Models for Temporal Clinical Transcriptomics Data

Timeseries clinical transcriptomic datasets offer the opportunity to gain insights into the dynamics of disease mechanisms/treatment responses. Howeve...

BiosInt: Biosensor-based smart design of pathway dynamic regulation for industrial biomanufacturing

Industrial-scale production of bio-based chemicals in the circular green bioeconomy still faces inefficiencies arising from scaling up challenges. Bio...

Integrating Machine Learning with Musculoskeletal Simulation Improves OpenCap Video-Based Dynamics Estimation

Musculoskeletal dynamics influence the progression and rehabilitation of many movement-related conditions. However, accurately estimating whole-body d...

Quantitative AI based on evolutionary computation and information theory combined with mathematical functions yields algorithmic RNA biomarkers from a randomized rheumatoid arthritis clinical trial, accurately predicting individual patient responses to anti-TNF treatment, to enable precision medicine

The routine derivation of novel biomarkers from therapeutic clinical trials to accurately predict individual patient’s responses, would be a significa...

Characterisation of 3000 patient reported outcomes with predictive machine learning to develop a scientific platform to study fatigue in Inflammatory Bowel Disease

Fatigue is commonly identified by IBD patients as major issue that affects their wellbeing. This presentation, however, is complex, multifactorial and...

Causal Forests versus Inverse Probability of Treatment Weighting to adjust for Cluster-Level Confounding: A Parametric and Plasmode Simulation Study based on US Hosptial Electronic Health Record Data

Rapid innovation and new regulations increase the need for post-marketing surveillance of implantable devices. However, complex multi-level confoundin...

A multi-modal vision knowledge graph of cardiovascular disease

Understanding gene-disease associations is important for uncovering pathological mechanisms and identifying potential therapeutic targets. Knowledge g...

Protective Dietary Antioxidants Intake Attenuate Cardiovascular-Kidney-Metabolic Syndrome Progression

Cardiovascular-kidney-metabolic (CKM) syndrome is characterized by complex pathophysiological interactions among cardiovascular diseases, and chronic ...