Latest AI and machine learning research in oncology/hematology for healthcare professionals.
Sleep staging is a crucial task in sleep monitoring and diagnosis, but clinical sleep staging is both time-consuming and subjective. In this study, we proposed a novel deep learning algorithm named feature fusion temporal convolutional network (FFTCN) for automatic sleep staging using single-channel EEG data. This algorithm employed a one-dimensional convolutional neural network (1D-CNN) to extrac...
INTRODUCTION: Individuals who develop new-onset diabetes have been identified as a high-risk cohort for pancreatic cancer (PC), exhibiting an incidence rate nearly 8 times higher than the general population. Hence, the targeted screening of this specific cohort presents a promising opportunity for early pancreatic cancer detection. We aimed to develop and validate a novel model capable of identify...
The mortality rate of oesophageal squamous cell carcinoma (ESCC) remains high, and conventional TNM systems cannot accurately predict its prognosis, t...
This study explores the potential use of ChatGPT, an AI-based language model, in assessing herbal-drug interactions (HDi) to enhance clinical decision...
INTRODUCTION: The aim of this study was to find the most appropriate variables to input into machine learning algorithms to identify those patients wi...
Programmed cell death (PCD) pathways hold significant influence in the etiology and progression of a variety of cancer forms, particularly offering pr...
As cancer cases continue to rise, with a 2023 study from Zhejiang and Harvard predicting a 31 percent increase in cases and a 21 percent increase in...
Brain tumors pose a serious health threat due to their rapid growth and potential for metastasis. While medical imaging has advanced significantly, ...
Recent advances in machine learning are transforming medical image analysis, particularly in cancer detection and classification. Techniques such as...
This study evaluates the generalisation capabilities of state-of-the-art histopathology foundation models on out-of-distribution multi-stain autoimm...
Biologists frequently desire protein inhibitors for a variety of reasons, including use as research tools for understanding biological processes and...
Esophageal squamous cell carcinoma (ESCC) is the most common histological type of esophageal cancer with a poor prognosis. Early diagnosis and prognos...
Infrared (IR) dyes, especially those within the near-infrared (NIR) spectrum, offer substantial advantages for in vivo imaging, owing to their deep ...
Lung cancer remains one of the leading causes of morbidity and mortality worldwide, making early diagnosis critical for improving therapeutic outcom...
Gallbladder cancer (GBC) is the most frequent cause of disease among biliary tract neoplasms. Identifying the molecular mechanisms and biomarkers li...
This study presented a novel approach for the precise ablation of breast tumors using focused ultrasound (FUS), leveraging a physics-informed neural n...
Automatic subphenotyping from electronic health records (EHRs)provides numerous opportunities to understand diseases with unique subgroups and enhan...
Brain tumor detection and classification are critical tasks in medical image analysis, particularly in early-stage diagnosis, where accurate and tim...
Data profiling has garnered increasing attention within the data science community, primarily focusing on structured data. In this paper, we introdu...
Leukemia, a severe form of blood cancer, claims thousands of lives each year. This study focuses on the detection of Acute Lymphoblastic Leukemia (A...