Survey of explainable AI techniques in healthcare
Artificial intelligence (AI) with deep learning models has been widely applied in numerous
domains, including medical imaging and healthcare tasks. In the medical field, any judgment …
domains, including medical imaging and healthcare tasks. In the medical field, any judgment …
[HTML][HTML] Predicting gene mutation status via artificial intelligence technologies based on multimodal integration (MMI) to advance precision oncology
J Shao, J Ma, Q Zhang, W Li, C Wang - Seminars in cancer biology, 2023 - Elsevier
Personalized treatment strategies for cancer frequently rely on the detection of genetic
alterations which are determined by molecular biology assays. Historically, these processes …
alterations which are determined by molecular biology assays. Historically, these processes …
Wearable flexible electronics based cardiac electrode for researcher mental stress detection system using machine learning models on single lead electrocardiogram …
In the modern world, wearable smart devices are continuously used to monitor people's
health. This study aims to develop an automatic mental stress detection system for …
health. This study aims to develop an automatic mental stress detection system for …
Predicting EGFR mutation status in non–small cell lung cancer using artificial intelligence: a systematic review and meta-analysis
Rationale and Objectives Recent advancements in artificial intelligence (AI) render a
substantial promise for epidermal growth factor receptor (EGFR) mutation status prediction …
substantial promise for epidermal growth factor receptor (EGFR) mutation status prediction …
Fusion of shallow and deep features from 18F-FDG PET/CT for predicting EGFR-sensitizing mutations in non-small cell lung cancer
Background Non-small cell lung cancer (NSCLC) patients with epidermal growth factor
receptor-sensitizing (EGFR-sensitizing) mutations exhibit a positive response to tyrosine …
receptor-sensitizing (EGFR-sensitizing) mutations exhibit a positive response to tyrosine …
Expanding role of advanced image analysis in CT-detected indeterminate pulmonary nodules and early lung cancer characterization
The implementation of low-dose chest CT for lung screening presents a crucial opportunity
to advance lung cancer care through early detection and interception. In addition, millions of …
to advance lung cancer care through early detection and interception. In addition, millions of …
Towards machine learning-aided lung cancer clinical routines: Approaches and open challenges
Advancements in the development of computer-aided decision (CAD) systems for clinical
routines provide unquestionable benefits in connecting human medical expertise with …
routines provide unquestionable benefits in connecting human medical expertise with …
Artificial intelligence methods available for cancer research
Cancer is a heterogeneous and multifaceted disease with a significant global footprint.
Despite substantial technological advancements for battling cancer, early diagnosis and …
Despite substantial technological advancements for battling cancer, early diagnosis and …
Comparing three-dimensional and two-dimensional deep-learning, radiomics, and fusion models for predicting occult lymph node metastasis in laryngeal squamous …
W Wang, H Liang, Z Zhang, C Xu, D Wei, W Li… - …, 2024 - thelancet.com
Background The occult lymph node metastasis (LNM) of laryngeal squamous cell carcinoma
(LSCC) affects the treatment and prognosis of patients. This study aimed to comprehensively …
(LSCC) affects the treatment and prognosis of patients. This study aimed to comprehensively …
Identification of endoplasmic reticulum stress-associated genes and subtypes for prediction of Alzheimer's disease based on interpretable machine learning
Y Lai, X Lin, C Lin, X Lin, Z Chen… - Frontiers in Pharmacology, 2022 - frontiersin.org
Introduction: Alzheimer's disease (AD) is a severe dementia with clinical and pathological
heterogeneity. Our study was aim to explore the roles of endoplasmic reticulum (ER) stress …
heterogeneity. Our study was aim to explore the roles of endoplasmic reticulum (ER) stress …