AI Medical Compendium Journal:
The oncologist

Showing 1 to 10 of 17 articles

Artificial Intelligence in Cancer Care: Legal and Regulatory Dimensions.

The oncologist
Considering that artificial intelligence (AI) technologies have the potential to change cancer care, this article discusses the AI features of which oncologist should most be aware.

Artificial Intelligence Systems Assisting Oncologists? Resist and Desist or Enlist and Coexist.

The oncologist
The use of artificial intelligence (AI) has become an integral part of patient care, but there are concerns about the impact of non‐human decision assistance on patient outcomes. This commentary focuses on how AI can assist oncologists and benefit pa...

Toward an Expert Level of Lung Cancer Detection and Classification Using a Deep Convolutional Neural Network.

The oncologist
BACKGROUND: Computed tomography (CT) is essential for pulmonary nodule detection in diagnosing lung cancer. As deep learning algorithms have recently been regarded as a promising technique in medical fields, we attempt to integrate a well-trained dee...

Applying Artificial Intelligence to Address the Knowledge Gaps in Cancer Care.

The oncologist
BACKGROUND: Rapid advances in science challenge the timely adoption of evidence-based care in community settings. To bridge the gap between what is possible and what is practiced, we researched approaches to developing an artificial intelligence (AI)...

Machine Learning for Better Prognostic Stratification and Driver Gene Identification Using Somatic Copy Number Variations in Anaplastic Oligodendroglioma.

The oncologist
BACKGROUND: 1p/19q-codeleted anaplastic gliomas have variable clinical behavior. We have recently shown that the common 9p21.3 allelic loss is an independent prognostic factor in this tumor type. The aim of this study is to identify less frequent gen...

Concordance with SPIRIT-AI guidelines in reporting of randomized controlled trial protocols investigating artificial intelligence in oncology: a systematic review.

The oncologist
BACKGROUND: Artificial intelligence (AI) is a promising tool used in oncology that may be able to facilitate diagnosis, treatment planning, and patient management. Transparency and completeness of protocols of randomized controlled trials (RCT) invol...

Ultrasound-based deep learning radiomics for enhanced axillary lymph node metastasis assessment: a multicenter study.

The oncologist
BACKGROUND: Accurate preoperative assessment of axillary lymph node metastasis (ALNM) in breast cancer is crucial for guiding treatment decisions. This study aimed to develop a deep-learning radiomics model for assessing ALNM and to evaluate its impa...

Medical accuracy of artificial intelligence chatbots in oncology: a scoping review.

The oncologist
BACKGROUND: Recent advances in large language models (LLM) have enabled human-like qualities of natural language competency. Applied to oncology, LLMs have been proposed to serve as an information resource and interpret vast amounts of data as a clin...

Epidemiology characteristics and clinical outcomes of composite Hodgkin lymphoma and diffuse large B-cell lymphoma using machine learning.

The oncologist
Composite lymphoma (CL) is rare. We conducted an analysis of 53 329 cases of diffuse large B-cell lymphoma (DLBCL), 17,916 cases of Hodgkin lymphoma (HL), and 869 cases of composite HL and DLBCL from the SEER database diagnosed between 2000 and 2019....

Predicting early recurrence of hepatocellular carcinoma after thermal ablation based on longitudinal MRI with a deep learning approach.

The oncologist
BACKGROUND: Accurate prediction of early recurrence (ER) is essential to improve the prognosis of patients with hepatocellular carcinoma (HCC) underwent thermal ablation (TA). Therefore, a deep learning model system using longitudinal magnetic resona...