Other Cancers

Artificial intelligence-based model for lymph node metastases detection on whole slide images in bladder cancer: a retrospective, multicentre, diagnostic study.

BACKGROUND: Accurate lymph node staging is important for the diagnosis and treatment of patients with bladder cancer. We aimed to develop a lymph node metastases diagnostic model (LNMDM) on whole slide images and to assess the clinical effect of an artificial intelligence-assisted (AI) workflow.

Artificial intelligence in cancer immunotherapy: Applications in neoantigen recognition, antibody design and immunotherapy response prediction.

Cancer immunotherapy is a method of controlling and eliminating tumors by reactivating the body's cancer-immunity cycle and restoring its antitumor immune response. The increased availability of data, combined with advancements in high-performance computing and innovative artificial intelligence (AI) technology, has resulted in a rise in the use of AI in oncology research. State-of-the-art AI mode...

Iodine maps derived from sparse-view kV-switching dual-energy CT equipped with a deep learning reconstruction for diagnosis of hepatocellular carcinoma.

Deep learning-based spectral CT imaging (DL-SCTI) is a novel type of fast kilovolt-switching dual-energy CT equipped with a cascaded deep-learning rec...

A Two-Stage End-to-End Deep Learning Framework for Pathologic Examination in Skin Tumor Diagnosis.

Neurofibromas (NFs), Bowen disease (BD), and seborrheic keratosis (SK) are common skin tumors. Pathologic examination is the gold standard for diagnos...

Predicting survival after radiosurgery in patients with lung cancer brain metastases using deep learning of radiomics and EGFR status.

The early prediction of overall survival (OS) in patients with lung cancer brain metastases (BMs) after Gamma Knife radiosurgery (GKRS) can facilitate...

Towards artificial intelligence to multi-omics characterization of tumor heterogeneity in esophageal cancer.

Esophageal cancer is a unique and complex heterogeneous malignancy, with substantial tumor heterogeneity: at the cellular levels, tumors are composed ...

An easy-to-use artificial intelligence preoperative lymph node metastasis predictor (LN-MASTER) in rectal cancer based on a privacy-preserving computing platform: multicenter retrospective cohort study.

BACKGROUND: Although the surgical treatment strategy for rectal cancer (RC) is usually based on the preoperative diagnosis of lymph node metastasis (L...

An Automatic Breast Tumor Detection and Classification including Automatic Tumor Volume Estimation Using Deep Learning Technique.

OBJECTIVE: This study aims to develop automatic breast tumor detection and classification including automatic tumor volume estimation using deep learn...

Application of Deep Learning System Technology in Identification of Women's Breast Cancer.

: The classification of breast cancer is performed based on its histological subtypes using the degree of differentiation. However, there have been lo...

Molecular and functional imaging in cancer-targeted therapy: current applications and future directions.

Targeted anticancer drugs block cancer cell growth by interfering with specific signaling pathways vital to carcinogenesis and tumor growth rather tha...

A real-time interpretable artificial intelligence model for the cholangioscopic diagnosis of malignant biliary stricture (with videos).

BACKGROUND AND AIMS: It is crucial to accurately determine malignant biliary strictures (MBSs) for early curative treatment. This study aimed to devel...

Effect of an Artificial Intelligence Decision Support Tool on Palliative Care Referral in Hospitalized Patients: A Randomized Clinical Trial.

CONTEXT: Palliative care services are commonly provided to hospitalized patients, but accurately predicting who needs them remains a challenge.

Diagnosing malignant distal bile duct obstruction using artificial intelligence based on clinical biomarkers.

Diagnosing distal bile duct obstruction remains challenging. This study aimed to examine the diagnostic ability of artificial intelligence (AI) based ...

Hepatocellular Carcinoma Recognition from Ultrasound Images Using Combinations of Conventional and Deep Learning Techniques.

Hepatocellular Carcinoma (HCC) is the most frequent malignant liver tumor and the third cause of cancer-related deaths worldwide. For many years, the ...

The devil is in the details: a small-lesion sensitive weakly supervised learning framework for prostate cancer detection and grading.

Prostate cancer (PCa) is a significant health concern in aging males, and the diagnosis depends primarily on histopathological assessments to determin...

Deep learning aided oropharyngeal cancer segmentation with adaptive thresholding for predicted tumor probability in FDG PET and CT images.

 Tumor segmentation is a fundamental step for radiotherapy treatment planning. To define an accurate segmentation of the primary tumor (GTVp) of oroph...

Cross-Domain Transfer of EEG to EEG or ECG Learning for CNN Classification Models.

Electroencephalography (EEG) is often used to evaluate several types of neurological brain disorders because of its noninvasive and high temporal reso...

Artificial intelligence and digital biomarker in precision pathology guiding immune therapy selection and precision oncology.

BACKGROUND: The currently available immunotherapies already changed the strategy how many cancers are treated from first to last line. Understanding e...

Artificial Intelligence in Brain Tumor Imaging: A Step toward Personalized Medicine.

The application of artificial intelligence (AI) is accelerating the paradigm shift towards patient-tailored brain tumor management, achieving optimal ...

Brain Tumor Segmentation and Classification from Sensor-Based Portable Microwave Brain Imaging System Using Lightweight Deep Learning Models.

Automated brain tumor segmentation from reconstructed microwave (RMW) brain images and image classification is essential for the investigation and mon...