Oncology/Hematology

Knowledge gaps in immune response and immunotherapy involving nanomaterials: Databases and artificial intelligence for material design.

Exploring the interactions between the immune system and nanomaterials (NMs) is critical for designing effective and safe NMs, but large knowledge gaps remain to be filled prior to clinical applications (e.g., immunotherapy). The lack of databases on interactions between the immune system and NMs affects the discovery of new NMs for immunotherapy. Complement activation and inhibition by NMs have b...

Machine learning analysis of DNA methylation in a hypoxia-immune model of oral squamous cell carcinoma.

BACKGROUND: Hypoxia status and immunity are related with the development and prognosis of oral squamous cell carcinoma (OSCC). Here, we constructed a hypoxia-immune model to explore its upstream mechanism and identify potential CpG sites.

Predicting Deep Learning Based Multi-Omics Parallel Integration Survival Subtypes in Lung Cancer Using Reverse Phase Protein Array Data.

Mortality attributed to lung cancer accounts for a large fraction of cancer deaths worldwide. With increasing mortality figures, the accurate predicti...

Artificial intelligence-based detection of lymph node metastases by PET/CT predicts prostate cancer-specific survival.

INTRODUCTION: Lymph node metastases are a key prognostic factor in prostate cancer (PCa), but detecting lymph node lesions from PET/CT images is a sub...

First clinical experience with single-port robotic transanal minimally invasive surgery (SP rTAMIS) for benign rectal neoplasms.

BACKGROUND: The new da Vinci Single-Port (SP) robot is a single-arm four-channel robotic system well suited for endoluminal surgery. We report our ini...

Oropharyngeal squamous cell carcinoma: radiomic machine-learning classifiers from multiparametric MR images for determination of HPV infection status.

We investigated the ability of machine-learning classifiers on radiomics from pre-treatment multiparametric magnetic resonance imaging (MRI) to accura...

Dermoscopic diagnostic performance of Japanese dermatologists for skin tumors differs by patient origin: A deep learning convolutional neural network closes the gap.

In the dermoscopic diagnosis of skin tumors, it remains unclear whether a deep neural network (DNN) trained with images from fair-skinned-predominant ...

AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia.

Coronavirus disease 2019 (COVID-19) emerged in 2019 and disseminated around the world rapidly. Computed tomography (CT) imaging has been proven to be ...

Artificial Intelligence and Its Role in Identifying Esophageal Neoplasia.

Randomized trials have demonstrated that ablation of dysplastic Barrett's esophagus can reduce the risk of progression to cancer. Endoscopic resection...

SHIFT: speedy histological-to-immunofluorescent translation of a tumor signature enabled by deep learning.

Spatially-resolved molecular profiling by immunostaining tissue sections is a key feature in cancer diagnosis, subtyping, and treatment, where it comp...

Magnetic resonance imaging-ultrasound fusion-targeted biopsy combined with systematic 12-core ultrasound-guided biopsy improves the detection of clinically significant prostate cancer: Are we ready to abandon the systematic approach?

BACKGROUND: Multiparametric (mp) magnetic resonance imaging (MRI)-ultrasound fusion-targeted biopsy (TB) has improved the detection of clinically sign...

Evaluation of a convolutional neural network for ovarian tumor differentiation based on magnetic resonance imaging.

OBJECTIVES: There currently lacks a noninvasive and accurate method to distinguish benign and malignant ovarian lesion prior to treatment. This study ...

Generating High-Quality Lymph Node Clinical Target Volumes for Head and Neck Cancer Radiation Therapy Using a Fully Automated Deep Learning-Based Approach.

PURPOSE: To develop a deep learning model that generates consistent, high-quality lymph node clinical target volumes (CTV) contours for head and neck ...

Identification and Staging of B-Cell Acute Lymphoblastic Leukemia Using Quantitative Phase Imaging and Machine Learning.

Identification and classification of leukemia cells in a rapid and label-free fashion is clinically challenging and thus presents a prime arena for im...

Feasibility, safety and efficacy of argon beam coagulation in robot-assisted partial nephrectomy for solid renal masses ≤ 7 cm in size.

One of the most important steps of the partial nephrectomy (PN) is hemostatic control of tumor bed which also effects the warm ischemia time (WIT). Ar...

The in vitro toxicity evaluation of halloysite nanotubes (HNTs) in human lung cells.

Halloysite nanotubes (HNTs) have been increasingly used in many industrial and biomedical fields. Therefore, the assessment of risk and consequences o...

Resection of the medial wall of the cavernous sinus in functioning pituitary adenomas: Technical note and outcomes in a matched-cohort study.

BACKGROUND: Parasellar dural invasion can be associated with treatment failure after excision of functioning pituitary adenomas. Because the medial wa...

Calcitonin Levels in Thyroid Disease Are Not Affected by Autoimmune Thyroiditis or Differentiated Thyroid Carcinoma.

INTRODUCTION: Association between hypercalcitoninemia and pathological conditions such as autoimmune thyroiditis (AIT) or differentiated thyroid carci...

An automatic EEG-based sleep staging system with introducing NAoSP and NAoGP as new metrics for sleep staging systems.

Different biological signals are recorded in sleep labs during sleep for the diagnosis and treatment of human sleep problems. Classification of sleep ...

Serum midkine levels for the diagnosis and assessment of response to interventional therapy in patients with hepatocellular carcinoma.

OBJECTIVE: To explore the clinical significance of serum midkine (MDK) levels for the diagnosis of hepatocellular carcinoma (HCC) and evaluate the eff...