AI-assisted detection of biomarkers by sensors and biosensors for early diagnosis and monitoring
T Wasilewski, W Kamysz, J Gębicki - Biosensors, 2024 - pmc.ncbi.nlm.nih.gov
The steady progress in consumer electronics, together with improvement in microflow
techniques, nanotechnology, and data processing, has led to implementation of cost …
techniques, nanotechnology, and data processing, has led to implementation of cost …
[HTML][HTML] Machine learning applications in precision medicine: overcoming challenges and unlocking potential
Precision medicine, utilizing genomic and phenotypic data, aims to tailor treatments for
individual patients. However, successful implementation into clinical practice is challenging …
individual patients. However, successful implementation into clinical practice is challenging …
Peptide clustering enhances large-scale analyses and reveals proteolytic signatures in mass spectrometry data
E Hartman, F Forsberg, S Kjellström, J Petrlova… - Nature …, 2024 - nature.com
Recent advances in mass spectrometry-based peptidomics have catalyzed the identification
and quantification of thousands of endogenous peptides across diverse biological systems …
and quantification of thousands of endogenous peptides across diverse biological systems …
Graph ai in medicine
In clinical artificial intelligence (AI), graph representation learning, mainly through graph
neural networks (GNNs), stands out for its capability to capture intricate relationships within …
neural networks (GNNs), stands out for its capability to capture intricate relationships within …
Graph Artificial Intelligence in Medicine
In clinical artificial intelligence (AI), graph representation learning, mainly through graph
neural networks and graph transformer architectures, stands out for its capability to capture …
neural networks and graph transformer architectures, stands out for its capability to capture …
The rise of scientific machine learning: a perspective on combining mechanistic modelling with machine learning for systems biology
Both machine learning and mechanistic modelling approaches have been used
independently with great success in systems biology. Machine learning excels in deriving …
independently with great success in systems biology. Machine learning excels in deriving …
Distinct soluble immune checkpoint profiles characterize COVID-19 severity, mortality and SARS-CoV-2 variant infections
Introduction Over the past four years, the COVID-19 pandemic has posed serious global
health challenges. The severe form of disease and death resulted from the failure of immune …
health challenges. The severe form of disease and death resulted from the failure of immune …
Computational methods and biomarker discovery strategies for spatial proteomics: a review in immuno-oncology
Advancements in imaging technologies have revolutionized our ability to deeply profile
pathological tissue architectures, generating large volumes of imaging data with …
pathological tissue architectures, generating large volumes of imaging data with …
Artificial intelligence in drug development
Drug development is a complex and time-consuming endeavor that traditionally relies on the
experience of drug developers and trial-and-error experimentation. The advent of artificial …
experience of drug developers and trial-and-error experimentation. The advent of artificial …
A mechanism-informed deep neural network enables prioritization of regulators that drive cell state transitions
Cells are regulated at multiple levels, from regulations of individual genes to interactions
across multiple genes. Some recent neural network models can connect molecular changes …
across multiple genes. Some recent neural network models can connect molecular changes …