Meditron-70b: Scaling medical pretraining for large language models
Large language models (LLMs) can potentially democratize access to medical knowledge.
While many efforts have been made to harness and improve LLMs' medical knowledge and …
While many efforts have been made to harness and improve LLMs' medical knowledge and …
[HTML][HTML] A defect-based physics-informed machine learning framework for fatigue finite life prediction in additive manufacturing
Defects in additively manufactured materials are one of the leading sources of uncertainty in
mechanical fatigue. Fracture mechanics concepts are useful to evaluate their influence …
mechanical fatigue. Fracture mechanics concepts are useful to evaluate their influence …
A fuzzy distance-based ensemble of deep models for cervical cancer detection
Abstract Background and Objective Cervical cancer is one of the leading causes of women's
death. Like any other disease, cervical cancer's early detection and treatment with the best …
death. Like any other disease, cervical cancer's early detection and treatment with the best …
Gradient-leakage resilient federated learning
Federated learning (FL) is an emerging distributed learning paradigm with default client
privacy because clients can keep sensitive data on their devices and only share local …
privacy because clients can keep sensitive data on their devices and only share local …
Deep learning-based automated forest health diagnosis from aerial images
Global climate change has had a drastic impact on our environment. Previous study showed
that pest disaster occured from global climate change may cause a tremendous number of …
that pest disaster occured from global climate change may cause a tremendous number of …
Boosting ensemble accuracy by revisiting ensemble diversity metrics
Neural network ensembles are gaining popularity by harnessing the complementary wisdom
of multiple base models. Ensemble teams with high diversity promote high failure …
of multiple base models. Ensemble teams with high diversity promote high failure …
Optimizing deep learning model parameters using socially implemented IoMT systems for diabetic retinopathy classification problem
Diabetic retinopathy (DR) is on the increase nowadays due to the high sugar level in the
blood, and it is the reason for blindness that mainly occurs in middle-aged people …
blood, and it is the reason for blindness that mainly occurs in middle-aged people …
Securing distributed sgd against gradient leakage threats
This paper presents a holistic approach to gradient leakage resilient distributed Stochastic
Gradient Descent (SGD). First, we analyze two types of strategies for privacy-enhanced …
Gradient Descent (SGD). First, we analyze two types of strategies for privacy-enhanced …
Two decades of bengali handwritten digit recognition: A survey
Handwritten Digit Recognition (HDR) is one of the most challenging tasks in the domain of
Optical Character Recognition (OCR). Irrespective of language, there are some inherent …
Optical Character Recognition (OCR). Irrespective of language, there are some inherent …
Evolving convolutional neural network parameters through the genetic algorithm for the breast cancer classification problem
K Davoudi, P Thulasiraman - Simulation, 2021 - journals.sagepub.com
Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer
mortality in women around the world. However, it can be controlled effectively by early …
mortality in women around the world. However, it can be controlled effectively by early …