Deep learning-enabled medical computer vision
A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the
potential for many fields—including medicine—to benefit from the insights that AI techniques …
potential for many fields—including medicine—to benefit from the insights that AI techniques …
Artificial intelligence in healthcare: review, ethics, trust challenges & future research directions
The use of artificial intelligence (AI) in medicine is beginning to alter current procedures in
prevention, diagnosis, treatment, amelioration, cure of disease and other physical and …
prevention, diagnosis, treatment, amelioration, cure of disease and other physical and …
Artificial intelligence in drug development: present status and future prospects
Highlights•Advances in artificial intelligence (AI) are modernising several aspects of our
lives.•The pharma industry is facing challenges to overcome the high attrition rates in drug …
lives.•The pharma industry is facing challenges to overcome the high attrition rates in drug …
A structure-based drug discovery paradigm
Structure-based drug design is becoming an essential tool for faster and more cost-efficient
lead discovery relative to the traditional method. Genomic, proteomic, and structural studies …
lead discovery relative to the traditional method. Genomic, proteomic, and structural studies …
Classification and diagnostic prediction of breast cancer metastasis on clinical data using machine learning algorithms
M Botlagunta, MD Botlagunta, MB Myneni… - Scientific Reports, 2023 - nature.com
Abstract Metastatic Breast Cancer (MBC) is one of the primary causes of cancer-related
deaths in women. Despite several limitations, histopathological information about the …
deaths in women. Despite several limitations, histopathological information about the …
Deep learning in drug discovery: opportunities, challenges and future prospects
A Lavecchia - Drug discovery today, 2019 - Elsevier
Highlights•Deep learning methods have gained outstanding achievements.•We review deep
learning methods/tools relevant to drug discovery research.•We discuss opportunities …
learning methods/tools relevant to drug discovery research.•We discuss opportunities …
Current strategies to address data scarcity in artificial intelligence-based drug discovery: A comprehensive review
Artificial intelligence (AI) has played a vital role in computer-aided drug design (CADD). This
development has been further accelerated with the increasing use of machine learning (ML) …
development has been further accelerated with the increasing use of machine learning (ML) …
Assessment of stored red blood cells through lab-on-a-chip technologies for precision transfusion medicine
Transfusion of red blood cells (RBCs) is one of the most valuable and widespread
treatments in modern medicine. Lifesaving RBC transfusions are facilitated by the cold …
treatments in modern medicine. Lifesaving RBC transfusions are facilitated by the cold …
Translational AI and deep learning in diagnostic pathology
There has been an exponential growth in the application of AI in health and in pathology.
This is resulting in the innovation of deep learning technologies that are specifically aimed at …
This is resulting in the innovation of deep learning technologies that are specifically aimed at …
COVID-19 diagnosis by routine blood tests using machine learning
Physicians taking care of patients with COVID-19 have described different changes in
routine blood parameters. However, these changes hinder them from performing COVID-19 …
routine blood parameters. However, these changes hinder them from performing COVID-19 …