AIMC Topic: Neoplasms

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Current trends and emerging themes in utilizing artificial intelligence to enhance anatomical diagnostic accuracy and efficiency in radiotherapy.

Progress in biomedical engineering (Bristol, England)
Artificial intelligence (AI) incorporation into healthcare has proven revolutionary, especially in radiotherapy, where accuracy is critical. The purpose of the study is to present patterns and develop topics in the application of AI to improve the pr...

Lexical associations can characterize clinical documentation trends related to palliative care and metastatic cancer.

Scientific reports
Palliative care is known to improve quality of life in advanced cancer. Natural language processing offers insights to how documentation around palliative care in relation to metastatic cancer has changed. We analyzed inpatient clinical notes using u...

Low-cost robotic manipulation of live microtissues for cancer drug testing.

Science advances
The scarcity of human biopsies available for drug testing is a paramount challenge for developing therapeutics, disease models, and personalized treatments. Microtechnologies that combine the microscale manipulation of tissues and fluids offer the ex...

Photon-counting CT in cancer radiotherapy: technological advances and clinical benefits.

Physics in medicine and biology
Photon-counting computed tomography (PCCT) marks a significant advancement over conventional Energy-integrating detector CT systems. This review highlights PCCT's superior spatial and contrast resolution, reduced radiation dose, and multi-energy imag...

Fake It till You Predict It: Data Augmentation Strategies to Detect Initiation and Termination of Oncology Treatment.

Studies in health technology and informatics
At the hospital, the dispersion of information regarding anti-cancer treatment makes it difficult to extract. We proposed a solution capable of identifying dates, drugs and their temporal relationship within free-text oncology reports with very few m...

Using Machine Learning for the Fusion of Tumor Records on a Real-World Dataset.

Studies in health technology and informatics
Cancer registries collect multiple reports describing the same tumor, potentially leading to duplicate or conflicting values across different records. This complicates further use of cancer data. Data fusion addresses this issue by consolidating mult...

Machine Learning Models Predicting Hospital Admissions During Chemotherapy Utilising Longitudinal Symptom Severity Reports and Patient-Reported Outcome Measures.

Studies in health technology and informatics
Chemotherapy toxicity can lead to acute hospital admissions, negatively impacting the healthcare system and patients' well-being. Machine learning (ML) models identifying patients at risk of emergency admissions are often developed on data lacking pa...

Building a Knowledge Base for Variant Annotation Using Therapy Recommendations in cBioPortal.

Studies in health technology and informatics
Molecular tumor boards present special challenges when it comes to information collection for case preparation. It is one of the most time-consuming tasks participating pathologists and oncologists face, limiting the number of cases that can be discu...

Machine Learning for Predicting Postoperative Functional Disability and Mortality Among Older Patients With Cancer: Retrospective Cohort Study.

JMIR aging
BACKGROUND: The global cancer burden is rapidly increasing, with 20 million new cases estimated in 2022. The world population aged ≥65 years is also increasing, projected to reach 15.9% by 2050, making cancer control for older patients urgent. Surgic...

Artificial Intelligence in Diagnostic Radiology: Where Do We Stand, Challenges, and Opportunities.

Journal of computer assisted tomography
Artificial intelligence (AI) is the most revolutionizing development in the health care industry in the current decade, with diagnostic imaging having the greatest share in such development. Machine learning and deep learning (DL) are subclasses of A...