Oncology/Hematology

Prediction of survival rate and effect of drugs on cancer patients with somatic mutations of genes: An AI-based approach.

The causal role of somatic mutation and its interrelationship with gene expression profile during tumor development has already been observed, which plays a major role to decide the cancer grades and overall survival. Accurate and robust prediction of tumor grades and patients' overall survival are important for prognosis, risk factors identification and betterment of the treatment strategy, espec...

Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study.

BACKGROUND: We examined the potential change in cancer detection when using an artificial intelligence (AI) cancer-detection software to triage certain screening examinations into a no radiologist work stream, and then after regular radiologist assessment of the remainder, triage certain screening examinations into an enhanced assessment work stream. The purpose of enhanced assessment was to simul...

Investigating the anti-angiogenic effects of Fufang Kushen Injection in combination with cisplatin using a zebrafish model.

The Traditional Chinese Medicine formula Fufang Kushen Injection (FKI) has demonstrated potential to enhance the efficacy and reduce the toxicity of t...

Comparative study of antibacterial activity between Schiff base nicotinic hydrazide derivative and its silver architected nanoparticles with atomic force microscopic study of bacterial cell wall.

The threat of multi-drug resistant bacterial pathogens evokes researchers to synthesized safe and effective chemotherapeutic agents for nano-drug deli...

A fatal invasive pulmonary infection in an adult patient with malignant lung adenocarcinoma.

BACKGROUND AND PURPOSE: complex as a ubiquitous environmental mold is increasingly reported to cause an invasive fungal infection in immunosuppressiv...

Comparison between atlas and convolutional neural network based automatic segmentation of multiple organs at risk in non-small cell lung cancer.

Delineation of organs at risk (OARs) is important but time consuming for radiotherapy planning. Automatic segmentation of OARs based on convolutional ...

[Artificial intelligence for cancer detection in breast cancer screening].

Artificial intelligence (AI) has the potential to increase quality and efficiency of breast cancer screening. Recent studies have provided comparative...

Concordance between treatment recommendations provided by IBM Watson for Oncology and a multidisciplinary tumor board for breast cancer in China.

OBJECTIVE: Watson for Oncology (WFO), an artificial intelligence from IBM Corporation, can provide a treatment plan by analyzing patient's disease cha...

Natural Language Processing in Dutch Free Text Radiology Reports: Challenges in a Small Language Area Staging Pulmonary Oncology.

Reports are the standard way of communication between the radiologist and the referring clinician. Efforts are made to improve this communication by, ...

Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms.

PURPOSE: Considerable progress has been made in the assessment and management of non-small cell lung cancer (NSCLC) patients based on mutation status ...

Segmentation of Masses on Mammograms Using Data Augmentation and Deep Learning.

The diagnosis of breast cancer in early stage is essential for successful treatment. Detection can be performed in several ways, the most common being...

Omitting Cortical Renorrhaphy in Robot-Assisted Partial Nephrectomy: Is it Safe? A Single Center Large Case Series.

Preserving renal function after robot-assisted partial nephrectomy (RAPN) is important and influenced by the technique of renal reconstruction among ...

Artificial intelligence in transplantation (machine-learning classifiers and transplant oncology).

PURPOSE OF REVIEW: To highlight recent efforts in the development and implementation of machine learning in transplant oncology - a field that uses li...

Prediagnostic Image Data, Artificial Intelligence, and Pancreatic Cancer: A Tell-Tale Sign to Early Detection.

Pancreatic cancer continues to be one of the deadliest malignancies and is the third leading cause of cancer-related mortality in the United States. B...

Prediction of immune checkpoint inhibition with immune oncology-related gene expression in gastrointestinal cancer using a machine learning classifier.

Immune checkpoint inhibitors (ICIs) have revolutionized the therapeutic landscape of gastrointestinal cancer. However, biomarkers correlated with the ...

Natural Language Processing of Serum Protein Electrophoresis Reports in the Veterans Affairs Health Care System.

PURPOSE: Serum protein electrophoresis (SPEP) is a clinical tool used to screen for monoclonal gammopathy, thus it is a critical tool in the evaluatio...

A refined cell-of-origin classifier with targeted NGS and artificial intelligence shows robust predictive value in DLBCL.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous entity of B-cell lymphoma. Cell-of-origin (COO) classification of DLBCL is required in routin...

A New Classification of Benign, Premalignant, and Malignant Endometrial Tissues Using Machine Learning Applied to 1413 Candidate Variables.

Benign normal (NL), premalignant (endometrial intraepithelial neoplasia, EIN) and malignant (cancer, EMCA) endometria must be precisely distinguished ...

Unsupervised machine learning and prognostic factors of survival in chronic lymphocytic leukemia.

OBJECTIVE: Unsupervised machine learning approaches hold promise for large-scale clinical data. However, the heterogeneity of clinical data raises new...

[Establishment and clinical testing of pancreatic cancer Faster R-CNN AI system based on fast regional convolutional neural network].

To investigate the effectiveness of an enhanced CT automatic recognition system based on Faster R-CNN for pancreatic cancer and its clinical value. ...