Oncology/Hematology

Fully end-to-end deep-learning-based diagnosis of pancreatic tumors.

Artificial intelligence can facilitate clinical decision making by considering massive amounts of medical imaging data. Various algorithms have been implemented for different clinical applications. Accurate diagnosis and treatment require reliable and interpretable data. For pancreatic tumor diagnosis, only 58.5% of images from the First Affiliated Hospital and the Second Affiliated Hospital, Zhej...

Assessing PD-L1 expression in non-small cell lung cancer and predicting responses to immune checkpoint inhibitors using deep learning on computed tomography images.

This study aimed to use computed tomography (CT) images to assess PD-L1 expression in non-small cell lung cancer (NSCLC) and predict response to immunotherapy. We retrospectively analyzed a PD-L1 expression dataset that consisted of 939 consecutive stage IIIB-IV NSCLC patients with pretreatment CT images. A deep convolutional neural network was trained and optimized with CT images from the train...

Application of radiomics and machine learning in head and neck cancers.

With the continuous development of medical image informatics technology, more and more high-throughput quantitative data could be extracted from digit...

Comparison of Robot-Assisted and Laparoscopic Partial Nephrectomy for Renal Hilar Tumors: Results from a Tertiary Referral Center.

To compare perioperative, functional, and oncologic outcomes between robot-assisted partial nephrectomy (RAPN) and laparoscopic partial nephrectomy (...

Pure and Hybrid Deep Learning Models can Predict Pathologic Tumor Response to Neoadjuvant Therapy in Pancreatic Adenocarcinoma: A Pilot Study.

BACKGROUND: Neoadjuvant therapy may improve survival of patients with pancreatic adenocarcinoma; however, determining response to therapy is difficult...

Small Steatotic HCC: A Radiological Variant Associated With Improved Outcome After Ablation.

Percutaneous thermal ablation is a validated treatment option for small hepatocellular carcinoma (HCC). Steatotic HCC can be reliably detected by magn...

Label-free metabolic clustering through unsupervised pixel classification of multiparametric fluorescent images.

Autofluorescence microscopy is a promising label-free approach to characterize NADH and FAD metabolites in live cells, with potential applications in ...

Porphyrin-based covalent organic framework as bioplatfrom for detection of vascular endothelial growth factor 165 through fluorescence resonance energy transfer.

A fluorescent aptasensor based on porphyrin-based covalent organic framework (p-COF) and carbon dots (CDs) was constructed for detecting vascular endo...

Semi-supervised learning for somatic variant calling and peptide identification in personalized cancer immunotherapy.

BACKGROUND: Personalized cancer vaccines are emerging as one of the most promising approaches to immunotherapy of advanced cancers. However, only a sm...

LASSO-Based Machine Learning Algorithm for Prediction of Lymph Node Metastasis in T1 Colorectal Cancer.

PURPOSE: The role of tumor-infiltrating lymphocytes (TILs) in predicting lymph node metastasis (LNM) in patients with T1 colorectal cancer (CRC) remai...

Deep learning-assisted magnetic resonance imaging prediction of tumor response to chemotherapy in patients with colorectal liver metastases.

Accurate evaluation of tumor response to preoperative chemotherapy is crucial for assigning appropriate patients with colorectal liver metastases (CRL...

Lung cancer survival period prediction and understanding: Deep learning approaches.

INTRODUCTION: Survival period prediction through early diagnosis of cancer has many benefits. It allows both patients and caregivers to plan resources...

DetexNet: Accurately Diagnosing Frequent and Challenging Pediatric Malignant Tumors.

The most frequent extracranial solid tumors of childhood, named peripheral neuroblastic tumors (pNTs), are very challenging to diagnose due to their d...

Striving for quality improvement: can artificial intelligence help?

Artificial intelligence (AI) is of keen interest for global health development as potential support for current human shortcomings. Gastrointestinal (...

Esophageal squamous dysplasia and cancer: Is artificial intelligence our best weapon?

Esophageal cancer is the eight most common cancer in the world and is associated with a poor prognosis. Significant efforts are necessary to improve t...

A novel gene expression test method of minimizing breast cancer risk in reduced cost and time by improving SVM-RFE gene selection method combined with LASSO.

Breast cancer is the leading diseases of death in women. It induces by a genetic mutation in breast cancer cells. Genetic testing has become popular t...

CellBox: Interpretable Machine Learning for Perturbation Biology with Application to the Design of Cancer Combination Therapy.

Systematic perturbation of cells followed by comprehensive measurements of molecular and phenotypic responses provides informative data resources for ...

Clinical Case Report: Dissociation of Clinical Course of Coexisting Autoimmune Hepatitis and Graves Disease.

OBJECTIVE: Concurrent autoimmune disorders, including autoimmune hepatitis (AIH), with Graves disease have been reported. Glucocorticoids can simultan...

Nonseminomatous Germ-Cell Tumor Presenting as Bilateral Adrenal Masses.

OBJECTIVE: Many tumors can metastasize to the adrenal glands, making the diagnosis of adrenal masses challenging. Awareness that rare primary tumors c...

Remission of Primary Hyperparathyroidism Following Fine-Needle Aspiration Biopsy: A Case Report and Review of the Literature.

BACKGROUND: Spontaneous or fine-needle aspiration biopsy (FNAB)-induced remission of primary hyperparathyroidism (PHPT) is an extremely rare and gener...