Oncology/Hematology

PBAC: A pathway-based attention convolution neural network for predicting clinical drug treatment responses.

Precise and personalized drug application is crucial in the clinical treatment of complex diseases. Although neural networks offer a new approach to improving drug strategies, their internal structure is difficult to interpret. Here, we propose PBAC (Pathway-Based Attention Convolution neural network), which integrates a deep learning framework and attention mechanism to address the complex biolog...

Navigating the Complexities of Artificial Intelligence-Enabled Real-World Data Collection for Oncology Pharmacovigilance.

This new editorial discusses the promise and challenges of successful integration of natural language processing methods into electronic health records for timely, robust, and fair oncology pharmacovigilance.

Applications of artificial intelligence in urologic oncology.

PURPOSE: With the recent rising interest in artificial intelligence (AI) in medicine, many studies have explored the potential and usefulness of AI in...

Clinical Validation of Artificial Intelligence-Powered PD-L1 Tumor Proportion Score Interpretation for Immune Checkpoint Inhibitor Response Prediction in Non-Small Cell Lung Cancer.

PURPOSE: Evaluation of PD-L1 tumor proportion score (TPS) by pathologists has been very impactful but is limited by factors such as intraobserver/inte...

Prognostic value of CDKN2A in head and neck squamous cell carcinoma via pathomics and machine learning.

This study aims to enhance the prognosis prediction of Head and Neck Squamous Cell Carcinoma (HNSCC) by employing artificial intelligence (AI) to anal...

Patient Characteristics Impact Performance of AI Algorithm in Interpreting Negative Screening Digital Breast Tomosynthesis Studies.

Background Artificial intelligence (AI) is increasingly used to manage radiologists' workloads. The impact of patient characteristics on AI performanc...

Use of Natural Language Understanding to Facilitate Surgical De-Escalation of Axillary Staging in Patients With Breast Cancer.

PURPOSE: Natural language understanding (NLU) may be particularly well equipped for enhanced data capture from the electronic health record given its ...

Use of Natural Language Processing to Infer Sites of Metastatic Disease From Radiology Reports at Scale.

PURPOSE: To evaluate natural language processing (NLP) methods to infer metastatic sites from radiology reports.

Extraction and Imputation of Eastern Cooperative Oncology Group Performance Status From Unstructured Oncology Notes Using Language Models.

PURPOSE: Eastern Cooperative Oncology Group (ECOG) performance status (PS) is a key clinical variable for cancer treatment and research, but it is usu...

Advances in applications of artificial intelligence algorithms for cancer-related miRNA research.

MiRNAs are a class of small non-coding RNAs, which regulate gene expression post-transcriptionally by partial complementary base pairing. Aberrant miR...

[Prediction of recurrence-free survival in lung adenocarcinoma based on self-supervised pre-training and multi-task learning].

Computed tomography (CT) imaging is a vital tool for the diagnosis and assessment of lung adenocarcinoma, and using CT images to predict the recurrenc...

Computed tomography-based radiomics to predict early recurrence of hepatocellular carcinoma post-hepatectomy in patients background on cirrhosis.

BACKGROUND: The prognosis for hepatocellular carcinoma (HCC) in the presence of cirrhosis is unfavourable, primarily attributable to the high incidenc...

Semi-Supervised, Attention-Based Deep Learning for Predicting TMPRSS2:ERG Fusion Status in Prostate Cancer Using Whole Slide Images.

Our study illuminates the potential of deep learning in effectively inferring key prostate cancer genetic alterations from the tissue morphology depic...

A novel single-port robot for total gastrectomy to treat gastric cancer: A case report (with video).

Multiport robots are now widely used for total gastrectomy for gastric cancer, while there is almost a void of research on whether single-port (SP) ro...

Robot-assisted laparoscopic surgery for rectal cancer in a patient with a horseshoe kidney: A case report.

A 52-year-old, Japanese man presented to the hospital with a complaint of anal bleeding, and detailed examination resulted in a diagnosis of locally a...

Advanced Technologies in Radiation Research.

The U.S. Government is committed to maintaining a robust research program that supports a portfolio of scientific experts who are investigating the bi...

Robot-assisted low anterior resection in a patient with rectal cancer who had a urinary reservoir: A case report.

Undergoing another surgery after a previous abdominal procedure can sometimes result in significant abdominal adhesions. We present a case of robot-as...

Feasibility and safety of robotic liver resection for huge (≥10 cm) hepatocellular carcinoma in a single centre: A propensity score-matched single-surgeon study.

BACKGROUND: The applicability of robot-assisted resection for huge hepatocellular carcinoma (HCC) of ≥10 cm remains contentious with limited available...

Construction and validation of artificial intelligence pathomics models for predicting pathological staging in colorectal cancer: Using multimodal data and clinical variables.

OBJECTIVE: This retrospective observational study aims to develop and validate artificial intelligence (AI) pathomics models based on pathological Hem...

Association Between Body Composition and Survival in Patients With Gastroesophageal Adenocarcinoma: An Automated Deep Learning Approach.

PURPOSE: Body composition (BC) may play a role in outcome prognostication in patients with gastroesophageal adenocarcinoma (GEAC). Artificial intellig...