Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions
Neurological disorders significantly outnumber diseases in other therapeutic areas.
However, developing drugs for central nervous system (CNS) disorders remains the most …
However, developing drugs for central nervous system (CNS) disorders remains the most …
Machine learning methods, databases and tools for drug combination prediction
L Wu, Y Wen, D Leng, Q Zhang, C Dai… - Briefings in …, 2022 - academic.oup.com
Combination therapy has shown an obvious efficacy on complex diseases and can greatly
reduce the development of drug resistance. However, even with high-throughput screens …
reduce the development of drug resistance. However, even with high-throughput screens …
SynergyFinder 3.0: an interactive analysis and consensus interpretation of multi-drug synergies across multiple samples
Abstract SynergyFinder (https://synergyfinder. fimm. fi) is a free web-application for
interactive analysis and visualization of multi-drug combination response data. Since its first …
interactive analysis and visualization of multi-drug combination response data. Since its first …
SynergyFinder 2.0: visual analytics of multi-drug combination synergies
Abstract SynergyFinder (https://synergyfinder. fimm. fi) is a stand-alone web-application for
interactive analysis and visualization of drug combination screening data. Since its first …
interactive analysis and visualization of drug combination screening data. Since its first …
[HTML][HTML] A benchmark study of deep learning-based multi-omics data fusion methods for cancer
D Leng, L Zheng, Y Wen, Y Zhang, L Wu, J Wang… - Genome biology, 2022 - Springer
Background A fused method using a combination of multi-omics data enables a
comprehensive study of complex biological processes and highlights the interrelationship of …
comprehensive study of complex biological processes and highlights the interrelationship of …
Introduction to artificial intelligence in ultrasound imaging in obstetrics and gynecology
Artificial intelligence (AI) uses data and algorithms to aim to draw conclusions that are as
good as, or even better than, those drawn by humans. AI is already part of our daily life; it is …
good as, or even better than, those drawn by humans. AI is already part of our daily life; it is …
A review of artificial intelligence applications for antimicrobial resistance
J Lv, S Deng, L Zhang - Biosafety and Health, 2021 - mednexus.org
The wide use and abuse of antibiotics could make antimicrobial resistance (AMR) an
increasingly serious issue that threatens global health and imposes an enormous burden on …
increasingly serious issue that threatens global health and imposes an enormous burden on …
Artificial intelligence and machine learning assisted drug delivery for effective treatment of infectious diseases
In the era of antimicrobial resistance, the prevalence of multidrug-resistant microorganisms
that resist conventional antibiotic treatment has steadily increased. Thus, it is now …
that resist conventional antibiotic treatment has steadily increased. Thus, it is now …
[HTML][HTML] Leveraging multi-way interactions for systematic prediction of pre-clinical drug combination effects
We present comboFM, a machine learning framework for predicting the responses of drug
combinations in pre-clinical studies, such as those based on cell lines or patient-derived …
combinations in pre-clinical studies, such as those based on cell lines or patient-derived …
[HTML][HTML] Harnessing machine learning to find synergistic combinations for FDA-approved cancer drugs
Combination therapy is a fundamental strategy in cancer chemotherapy. It involves
administering two or more anti-cancer agents to increase efficacy and overcome multidrug …
administering two or more anti-cancer agents to increase efficacy and overcome multidrug …