Explainable artificial intelligence for drug discovery and development-a comprehensive survey
The field of drug discovery has experienced a remarkable transformation with the advent of
artificial intelligence (AI) and machine learning (ML) technologies. However, as these AI and …
artificial intelligence (AI) and machine learning (ML) technologies. However, as these AI and …
Mode of action of biogenic silver, zinc, copper, titanium and cobalt nanoparticles against antibiotics resistant pathogens
The rapid surge in antibiotic resistance to pathogens has emerged as a grave threat to
public health, globally. This multiple drug resistance (MDR) is directly linked to the high rates …
public health, globally. This multiple drug resistance (MDR) is directly linked to the high rates …
A separable temporal convolutional networks based deep learning technique for discovering antiviral medicines
An alarming number of fatalities caused by the COVID-19 pandemic has forced the scientific
community to accelerate the process of therapeutic drug discovery. In this regard, the …
community to accelerate the process of therapeutic drug discovery. In this regard, the …
Continual learning in medical imaging analysis: A comprehensive review of recent advancements and future prospects
Medical imaging analysis has witnessed remarkable advancements even surpassing
human-level performance in recent years, driven by the rapid development of advanced …
human-level performance in recent years, driven by the rapid development of advanced …
Artificial intelligence-based model for predicting the minimum inhibitory concentration of antibacterial peptides against ESKAPEE pathogens
R Sharma, S Shrivastava, SK Singh… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
In response to environmental threats, pathogens make several changes in their genome,
leading to antimicrobial resistance (AMR). Due to AMR, the pathogens do not respond to …
leading to antimicrobial resistance (AMR). Due to AMR, the pathogens do not respond to …
Overcoming catastrophic forgetting in molecular property prediction using continual learning of sequential episodes
S Ranjan, SK Singh - Expert Systems with Applications, 2024 - Elsevier
Abstract Continual Learning requires Large Language Models (LLM) to adapt to new
episodes and data over time without forgetting the knowledge acquired from previous …
episodes and data over time without forgetting the knowledge acquired from previous …
Multi-label classification to predict antibiotic resistance from raw clinical MALDI-TOF mass spectrometry data
CA Astudillo, XA López-Cortés, E Ocque… - Scientific Reports, 2024 - nature.com
Antimicrobial resistance (AMR) poses a significant global health challenge, necessitating
advanced predictive models to support clinical decision-making. In this study, we explore …
advanced predictive models to support clinical decision-making. In this study, we explore …
Multiscale Temporal Convolutional Network-Based End-to-End Recognition of Drill-String Stick-Slip Vibration in Drilling Process
Severe drill-string vibration is a significant source of drilling problems. Most existing methods
for vibration recognition rely on downhole data, facing great limitations in practice. In …
for vibration recognition rely on downhole data, facing great limitations in practice. In …
Designing new blood-brain barrier penetrating molecules using novel hybridized gravitational search algorithm and explainable AI
Artificial intelligence (AI) has emerged as a powerful tool in computational biology, where it
is being used to analyze large datasets to detect difficult biological patterns. This has …
is being used to analyze large datasets to detect difficult biological patterns. This has …
Antibiotic Bacteria Interaction: Dataset and Benchmarking.
S Chatterjee, A Majumdar, E Chouzenoux - bioRxiv, 2024 - biorxiv.org
This study introduces a dataset for drug-bacteria associations (DBA) that affects humans.
Our contribution extends beyond merely curating the association matrix; we also conduct …
Our contribution extends beyond merely curating the association matrix; we also conduct …