[HTML][HTML] Ai in thyroid cancer diagnosis: Techniques, trends, and future directions
Artificial intelligence (AI) has significantly impacted thyroid cancer diagnosis in recent years,
offering advanced tools and methodologies that promise to revolutionize patient outcomes …
offering advanced tools and methodologies that promise to revolutionize patient outcomes …
[HTML][HTML] Machine learning and deep learning-based approach in smart healthcare: Recent advances, applications, challenges and opportunities
In recent years, machine learning (ML) and deep learning (DL) have been the leading
approaches to solving various challenges, such as disease predictions, drug discovery …
approaches to solving various challenges, such as disease predictions, drug discovery …
Application of semi-supervised learning in image classification: Research on fusion of labeled and unlabeled data
Deep learning has attracted wide attention recently because of its excellent feature
representation ability and end-to-end automatic learning method. Especially in clinical …
representation ability and end-to-end automatic learning method. Especially in clinical …
[HTML][HTML] An advanced deep neural network for fundus image analysis and enhancing diabetic retinopathy detection
Diabetic retinopathy (DR) involves retina damage due to diabetes, often leading to
blindness. It is diagnosed via color fundus injections, but the manual analysis is …
blindness. It is diagnosed via color fundus injections, but the manual analysis is …
Equilibrium optimization algorithm with deep learning enabled prostate cancer detection on MRI images
The enlargement of the prostate gland in the reproductive system of males is considered a
form of prostate cancer (PrC). The survival rate is considerably improved with earlier …
form of prostate cancer (PrC). The survival rate is considerably improved with earlier …
Evaluating Retinal Disease Diagnosis with an Interpretable Lightweight CNN Model Resistant to Adversarial Attacks
Optical Coherence Tomography (OCT) is an imperative symptomatic tool empowering the
diagnosis of retinal diseases and anomalies. The manual decision towards those anomalies …
diagnosis of retinal diseases and anomalies. The manual decision towards those anomalies …
Explainable AI evaluation: a top-down approach for selecting optimal explanations for black box models
Explainable Artificial Intelligence (XAI) evaluation has grown significantly due to its
extensive adoption, and the catastrophic consequence of misinterpreting sensitive data …
extensive adoption, and the catastrophic consequence of misinterpreting sensitive data …
Comparative Analysis Of AI Regression And Classification Models For Predicting House Damages İn Nepal: Proposed Architectures And Techniques
This paper proposes a machine-learning model for earthquake prediction. Earthquakes are
complex and unpredictable natural phenomena, making it challenging to predict them …
complex and unpredictable natural phenomena, making it challenging to predict them …
Dynamic Clustering Strategies Boosting Deep Learning in Olive Leaf Disease Diagnosis
AH Alsaeedi, AM Al-juboori, HHR Al-Mahmood… - Sustainability, 2023 - mdpi.com
Artificial intelligence has many applications in various industries, including agriculture. It can
help overcome challenges by providing efficient solutions, especially in the early stages of …
help overcome challenges by providing efficient solutions, especially in the early stages of …
[PDF][PDF] Tomato disease recognition: Advancing accuracy through xception and bilinear pooling fusion
Accurate detection and classification of tomato diseases are essential for effective disease
management and maintaining agricultural productivity. This paper presents a novel …
management and maintaining agricultural productivity. This paper presents a novel …