AIMC Topic: Early Detection of Cancer

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Generating research hypotheses to overcome key challenges in the early diagnosis of colorectal cancer - Future application of AI.

Cancer letters
We intend to explore the capability of ChatGPT 4.0 in generating innovative research hypotheses to address key challenges in the early diagnosis of colorectal cancer (CRC). We asked ChatGPT to generate hypotheses focusing on three main challenges: im...

Wearable device for axillary lymph node screening in breast cancer based on infrared thermography and artificial intelligence.

Breast cancer research : BCR
BACKGROUND: Breast cancer (BC) is the most prevalent cancer among women worldwide, and patients with metastasis to axillary lymph nodes (ALN) experience significantly lower survival rates. Current imaging-based screening methods often suffer from low...

Enhanced Early Detection of Colorectal Cancer via Blood Biomarker Combinations Identified Through Extracellular Vesicle Isolation and Artificial Intelligence Analysis.

Journal of extracellular vesicles
Colorectal cancer (CRC) remains a major cause of cancer-related deaths worldwide, with early detection being crucial for improving survival rates. Despite the potential of extracellular vesicles (EVs) as blood biomarkers for CRC diagnosis, their clin...

Four Different Artificial Intelligence Models Logistic Regression to Enhance the Diagnostic Accuracy of Fecal Immunochemical Test in the Detection of Colorectal Carcinoma in a Screening Setting.

Anticancer research
BACKGROUND/AIM: This study aimed to evaluate the diagnostic accuracy (DA) of four artificial intelligence (AI) models compared to logistic regression (LR) in enhancing the performance of the fecal immunochemical test (FIT) for the detection of colore...

Rapid and Noninvasive Early Detection of Lung Cancer by Integration of Machine Learning and Salivary Metabolic Fingerprints Using MS LOC Platform: A Large-Scale Multicenter Study.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Most lung cancer (LC) patients are diagnosed at advanced stages due to the lack of effective screening tools. This multicenter study analyzes 1043 saliva samples (334 LC cases and 709 non-LC cases) using a novel high-throughput platform for metabolic...

The present and future of lung cancer screening: latest evidence.

Future oncology (London, England)
Lung cancer is the leading cause of cancer-related mortality worldwide. Early lung cancer detection improves lung cancer-related mortality and survival. This report summarizes presentations and panel discussions from a webinar, "The Present and Futur...

Broadening the Net: Overcoming Challenges and Embracing Novel Technologies in Lung Cancer Screening.

American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting
Lung cancer is one of the leading causes of cancer-related mortality worldwide, with most cases diagnosed at advanced stages where curative treatment options are limited. Low-dose computed tomography (LDCT) for lung cancer screening (LCS) of individu...

Enhanced non-invasive machine learning approach for early colorectal cancer detection: Predictive modeling and validation in a Jordanian cohort.

Computers in biology and medicine
BACKGROUND: Colorectal cancer (CRC) ranks as the third most prevalent cancer worldwide, posing significant public health challenges. Late-stage detection often results in poor treatment outcomes, elevating mortality rates. The economic and psychologi...

Artificial intelligence-driven microRNA signature for early detection of gastric cancer: discovery and clinical functional exploration.

British journal of cancer
BACKGROUND: Gastric cancer (GC) is a leading cause of cancer-related deaths worldwide, with late-stage diagnoses frequently leading to poor outcomes. This underscores the need for effective early-stage gastric cancer (ESGC) diagnostics.

Review and reflections on live AI mammographic screen reading in a large UK NHS breast screening unit.

Clinical radiology
UNLABELLED: The Radiology team from a large Breast Screening Unit in the UK with a screening population of over 135,000 took part in a service evaluation project using artificial intelligence (AI) for reading breast screening mammograms.