Oncology/Hematology

Radiation oncology 2.0.

Machine Learning for Early Lung Cancer Identification Using Routine Clinical and Laboratory Data.

Most lung cancers are diagnosed at an advanced stage. Presymptomatic identification of high-risk individuals can prompt earlier intervention and improve long-term outcomes. To develop a model to predict a future diagnosis of lung cancer on the basis of routine clinical and laboratory data by using machine learning. We assembled data from 6,505 case patients with non-small cell lung cancer (NSCL...

Transanal Minimally Invasive Surgery: A Useful Technique That Continues to Evolve.

Colorectal cancer remains the 3rd most common cancer diagnosed among men and women in the United States. With improved screening, premalignant rectal ...

[Interactions between radical prostatovesiculectomy and diagnosis of prostate cancer : A medical-historical inventory on the occasion of 20 years of robot-assisted treatment].

The question of what came first-in this case the diagnosis of prostate cancer or its therapy-seems absurd at first glance and is reminiscent of the cl...

Artificial Intelligence in Imaging of Chronic Liver Diseases: Current Update and Future Perspectives.

Here we review artificial intelligence (AI) models which aim to assess various aspects of chronic liver disease. Despite the clinical importance of he...

Ethics and standards in the use of artificial intelligence in medicine on behalf of the Royal Australian and New Zealand College of Radiologists.

INTRODUCTION: The Royal Australian and New Zealand College of Radiologists (RANZCR) led the medical community in Australia and New Zealand in consider...

Automatic detection of oral cancer in smartphone-based images using deep learning for early diagnosis.

SIGNIFICANCE: Oral cancer is a quite common global health issue. Early diagnosis of cancerous and potentially malignant disorders in the oral cavity w...

Prediction of Neutropenic Events in Chemotherapy Patients: A Machine Learning Approach.

PURPOSE: Severe and febrile neutropenia present serious hazards to patients with cancer undergoing chemotherapy. We seek to develop a machine learning...

Early Detection of Pancreatic Cancer: Applying Artificial Intelligence to Electronic Health Records.

The potential of artificial intelligence (AI) applied to clinical data from electronic health records (EHRs) to improve early detection for pancreatic...

Machine learning application identifies novel gene signatures from transcriptomic data of spontaneous canine hemangiosarcoma.

Angiosarcomas are soft-tissue sarcomas that form malignant vascular tissues. Angiosarcomas are very rare, and due to their aggressive behavior and hig...

Identification of pan-cancer Ras pathway activation with deep learning.

The identification of hidden responders is often an essential challenge in precision oncology. A recent attempt based on machine learning has been pro...

DeepSSV: detecting somatic small variants in paired tumor and normal sequencing data with convolutional neural network.

It is of considerable interest to detect somatic mutations in paired tumor and normal sequencing data. A number of callers that are based on statistic...

Large-scale comparative review and assessment of computational methods for anti-cancer peptide identification.

Anti-cancer peptides (ACPs) are known as potential therapeutics for cancer. Due to their unique ability to target cancer cells without affecting healt...

Unveiling the immune infiltrate modulation in cancer and response to immunotherapy by MIXTURE-an enhanced deconvolution method.

The accurate quantification of tumor-infiltrating immune cells turns crucial to uncover their role in tumor immune escape, to determine patient progno...

Highly accurate diagnosis of papillary thyroid carcinomas based on personalized pathways coupled with machine learning.

Thyroid nodules are neoplasms commonly found among adults, with papillary thyroid carcinoma (PTC) being the most prevalent malignancy. However, curren...

A graph auto-encoder model for miRNA-disease associations prediction.

Emerging evidence indicates that the abnormal expression of miRNAs involves in the evolution and progression of various human complex diseases. Identi...

Applications of artificial intelligence in prostate cancer imaging.

PURPOSE OF REVIEW: The purpose of this review was to identify the most recent lines of research focusing on the application of artificial intelligence...

Accurate diagnosis of endoscopic mucosal healing in ulcerative colitis using deep learning and machine learning.

BACKGROUND: In clinical applications, mucosal healing is a therapeutic goal in patients with ulcerative colitis (UC). Endoscopic remission is associat...

Artificial Intelligence in Diagnostic Imaging and Radiation Therapy.

Artificial intelligence (AI) is a rapidly growing profession that shows continued promise for diagnostic imaging in various disciplines, including der...

Unsupervised flow cytometry analysis in hematological malignancies: A new paradigm.

Ever since hematopoietic cells became "events" enumerated and characterized in suspension by cell counters or flow cytometers, researchers and enginee...