AIMC Topic: Early Detection of Cancer

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Cost-effectiveness of a machine learning risk prediction model (LungFlag) in the selection of high-risk individuals for non-small cell lung cancer screening in Spain.

Journal of medical economics
OBJECTIVE: The LungFlag risk prediction model uses individualized clinical variables to identify individuals at high-risk of non-small cell lung cancer (NSCLC) for screening with low-dose computed tomography (LDCT). This study evaluates the cost-effe...

Breast cancer early detection and molecular subtype prediction by combination of Raman spectroscopy with deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Breast cancer is one of the most common tumors in women, and early screening can significantly reduce mortality rates. Meanwhile, accurately identifying HER2-positive and HER2-negative subtypes of breast cancer is critical for helping doctors determi...

Modeling Early-Onset Cancer Kinetics Reveals Changes in Underlying Risk and the Impact of Population Screening.

Cancer research
UNLABELLED: Recent studies have reported increases in early-onset cancer cases (diagnosed less than 50 years of age) and raised questions about whether the increase is related to earlier diagnosis from nonspecific medical tests as reflected by decrea...

Emerging biomarkers for pancreatic cancer: from early detection to personalized therapy.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
Pancreatic cancer (PC) remains one of the most lethal malignancies, primarily due to its poor prognosis and late diagnosis. Biomarkers are essential in enhancing diagnostic accuracy, prognostic assessments, and therapeutic strategies, thereby address...

Sex-specific prognostic value of automated epicardial adipose tissue quantification on serial lung cancer screening chest computed tomography.

European heart journal. Cardiovascular Imaging
AIMS: Epicardial adipose tissue (EAT) is a metabolically active fat depot associated with coronary atherosclerosis and cardiovascular (CV) risk. While EAT is a known prognostic marker in lung cancer screening, its sex-specific prognostic value remain...

Framework to Select Multi-Cancer Detection Assays in the National Cancer Institute's Vanguard Study.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
BACKGROUND: The Cancer Screening Research Network is a new clinical trials network funded by the NCI. The first Cancer Screening Research Network study, the Vanguard Study (VS), will assess the feasibility of using multi-cancer detection (MCD) tests ...

Deciphering the molecular fingerprint of haemoglobin in lung cancer: A new strategy for early diagnosis using two-trace two-dimensional correlation near infrared spectroscopy (2T2D-NIRS) and machine learning techniques.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Lung cancer remains one of the deadliest malignancies worldwide, highlighting the need for highly sensitive and minimally invasive early diagnostic methods. Near-infrared spectroscopy (NIRS) offers unique advantages in probing molecular vibrational i...

CervicalMethDx: A Precision DNA Methylation Test to Identify Risk of High-Grade Intraepithelial Lesions in Cervical Cancer Screening Algorithms.

Cancer prevention research (Philadelphia, Pa.)
UNLABELLED: Cervical cancer is one of the most common cancers in women. Despite progress in prevention and success in early detection through cytologic screening and human papillomavirus (HPV) detection, there remains a challenge in triaging women ap...

Development of a deep learning-based automated diagnostic system (DLADS) for classifying mammographic lesions - a first large-scale multi-institutional clinical trial in Japan.

Breast cancer (Tokyo, Japan)
BACKGROUND: Recently, western countries have built evidence on mammographic artificial Intelligence-computer-aided diagnosis (AI-CADx) systems; however, their effectiveness has not yet been sufficiently validated in Japanese women. In this study, we ...

Combining structural equation modeling analysis with machine learning for early malignancy detection in Bethesda Category III thyroid nodules.

Artificial intelligence in medicine
Atypia of Undetermined Significance (AUS), classified as Category III in the Bethesda Thyroid Cytopathology Reporting System, presents significant diagnostic challenges for clinicians. This study aims to develop a clinical decision support system tha...