2 天前 - … In recent years, deep learning became very popular and to a certain extend it
delivered promising results. However, it has certain flaws that might lead to misclassification. The …

2 天前 - … that use deep learning to estimate 2D keypoint from images have emerged as a
promising alternative, but annotation errors in training datasets used by deep learning models …

2 天前 - … Image analysis can play an important role in supporting histopathological diagnoses
of lung cancer, with deep learning methods already achieving remarkable results. However…

5 天前 - … populations and comparatively few healthcare professionals, there is a dire need
for AI-enabled systems using Machine Learning (ML) and Deep Learning (DL) models for the …

5 天前 - … [33] present that deep learning gains prominence in medical image analysis, and
explainability becomes crucial. Thus, DL-based medical image analysis through XAI and …

5 天前 - … Conventional machine learning (ML) algorithms applied to microbiome-based
CRC detection often yield suboptimal accuracy. Conversely, deep neural network (DNN)-based …

5 天前 - … layers are what deep learning algorithms are made of. Some deep learning models
have been shown to outperform well-known machine learning and quantitative structure-…

5 天前 - … previously veiled within the opaque construct of deep learning’s black box model.
This … on constructing intelligible deep learning models tailored for patient data analytics. …

5 天前 - … Furthermore, the proposed architecture sets a precedent for integrating intricate
deep learning models into medical handheld devices. Implementing this approach offers a …

5 天前 - … on a branch of ML known as Deep Learning (DL), in which … of deep learning
algorithms in fields such as healthcare, … Deep learning providers can research, test, and operate …