Oncology/Hematology

Computer-Aided Diagnosis Systems in Diagnosing Malignant Thyroid Nodules on Ultrasonography: A Systematic Review and Meta-Analysis.

BACKGROUND: Computer-aided diagnosis (CAD) systems are being applied to the ultrasonographic diagnosis of malignant thyroid nodules, but it remains controversial whether the systems add any accuracy for radiologists.

Automated oral squamous cell carcinoma identification using shape, texture and color features of whole image strips.

Despite profound knowledge of the incidence of oral cancers and a large body of research beyond it, it continues to beat diagnosis and treatment management. Post physical observation by clinicians, a biopsy is a gold standard for accurate detection of any abnormalities. Towards the application of artificial intelligence as an aid to diagnosis, automated cell nuclei segmentation is the most essenti...

Twin Robotic X-Ray System for 3D Cone-Beam CT of the Wrist: An Evaluation of Image Quality and Radiation Dose.

The purpose of this study was to assess image quality and radiation dose of a novel twin robotic x-ray system's 3D cone-beam CT (CBCT) function for t...

Machine Learning Models Based on Molecular Fingerprints and an Extreme Gradient Boosting Method Lead to the Discovery of JAK2 Inhibitors.

Developing Janus kinase 2 (JAK2) inhibitors has become a significant focus for small-molecule drug discovery programs in recent years because the inhi...

Interaction of apigenin-7-O-glucoside with pyrimethamine against growth.

Apigenin-7-O-glucoside, a flavonoid glucoside known to inhibit cancer cell growth, fungi growth, both intra and extracellular reactive oxygen species ...

Liver tumor segmentation based on 3D convolutional neural network with dual scale.

PURPOSE: Liver is one of the organs with a high incidence of tumors in the human body. Malignant liver tumors seriously threaten human life and health...

Liver tumor segmentation in CT volumes using an adversarial densely connected network.

BACKGROUND: Malignant liver tumor is one of the main causes of human death. In order to help physician better diagnose and make personalized treatment...

The integrative knowledge base for miRNA-mRNA expression in colorectal cancer.

"miRNA colorectal cancer" (https://mirna-coadread.omics.si/) is a freely available web application for studying microRNA and mRNA expression and their...

CDSeq: A novel complete deconvolution method for dissecting heterogeneous samples using gene expression data.

Quantifying cell-type proportions and their corresponding gene expression profiles in tissue samples would enhance understanding of the contributions ...

Evaluation of colorectal cancer subtypes and cell lines using deep learning.

Colorectal cancer (CRC) is a common cancer with a high mortality rate and a rising incidence rate in the developed world. Molecular profiling techniqu...

Evolving the pulmonary nodules diagnosis from classical approaches to deep learning-aided decision support: three decades' development course and future prospect.

PURPOSE: Lung cancer is the commonest cause of cancer deaths worldwide, and its mortality can be reduced significantly by performing early diagnosis a...

Clinical calculator predictive of chemotherapy benefit in stage 1A uterine papillary serous cancers.

OBJECTIVE: Determine the utility of a clinical calculator to predict the benefit of chemotherapy in stage IA uterine papillary serous cancer (UPSC).

Standard operating procedure for curation and clinical interpretation of variants in cancer.

Manually curated variant knowledgebases and their associated knowledge models are serving an increasingly important role in distributing and interpret...

Methylglyoxal-derived advanced glycation end products induce matrix metalloproteinases through activation of ERK/JNK/NF-κB pathway in kidney proximal epithelial cells.

The accumulation of reactive α-dicarbonyl leading to advanced glycation end products (AGEs) have been linked to pathophysiological diseases in many st...

SGL-SVM: A novel method for tumor classification via support vector machine with sparse group Lasso.

At present, with the in-depth study of gene expression data, the significant role of tumor classification in clinical medicine has become more apparen...

The role of artificial intelligence in medical imaging research.

Without doubt, artificial intelligence (AI) is the most discussed topic today in medical imaging research, both in diagnostic and therapeutic. For dia...

Dissection of gene expression datasets into clinically relevant interaction signatures via high-dimensional correlation maximization.

Gene expression is controlled by many simultaneous interactions, frequently measured collectively in biology and medicine by high-throughput technolog...

Machine Learning Approaches to Radiogenomics of Breast Cancer using Low-Dose Perfusion Computed Tomography: Predicting Prognostic Biomarkers and Molecular Subtypes.

Radiogenomics investigates the relationship between imaging phenotypes and genetic expression. Breast cancer is a heterogeneous disease that manifests...

Histopathology-guided mass spectrometry differentiates benign nevi from malignant melanoma.

PURPOSE: Distinguishing benign nevi from malignant melanoma using current histopathological criteria may be very challenging and is one the most diffi...

Comparative clinical evaluation of atlas and deep-learning-based auto-segmentation of organ structures in liver cancer.

BACKGROUND: Accurate and standardized descriptions of organs at risk (OARs) are essential in radiation therapy for treatment planning and evaluation. ...