4.6 Article

Machine Learning for the Prediction of Synchronous Organ-Specific Metastasis in Patients With Lung Cancer

Related references

Note: Only part of the references are listed.
Article Radiology, Nuclear Medicine & Medical Imaging

Identification of predictors for brain metastasis in newly diagnosed non-small cell lung cancer: a single-center cohort study

Sohee Park et al.

Summary: Clinical and staging chest CT characteristics play an important role in predicting brain metastasis in patients with newly diagnosed NSCLC, with distinct predictors identified for resectable and unresectable stages. Factors such as age, sex, extrathoracic metastasis, lung cancer subtypes, and EGFR mutations were associated with brain metastasis in these patients.

EUROPEAN RADIOLOGY (2022)

Article Oncology

Development of robust artificial neural networks for prediction of 5-year survival in bladder cancer

Hriday P. Bhambhvani et al.

Summary: Compared to conventional statistical methods, machine learning algorithms improve the accuracy of predicting survival outcomes for bladder cancer patients, particularly in overall survival. Artificial neural networks outperform multivariable Cox proportional hazards models in predicting disease-specific survival with similar accuracy.

UROLOGIC ONCOLOGY-SEMINARS AND ORIGINAL INVESTIGATIONS (2021)

Article Medicine, Research & Experimental

Diagnostic and prognostic nomograms for bone metastasis in small cell lung cancer

Chenan Liu et al.

Summary: The study retrospectively analyzed 18,187 cases of small cell lung cancer, finding that patients with bone metastasis had significantly lower survival rates than those without bone metastasis. Factors such as age, gender, tumor size, N stage, chemotherapy, surgery, radiotherapy, and liver/brain/lung metastases were related to bone metastasis and independently affected patient survival.

JOURNAL OF INTERNATIONAL MEDICAL RESEARCH (2021)

Article Oncology

Factors for incidence risk and prognosis in non-small-cell lung cancer patients with synchronous brain metastasis: a population-based study

Haizhen Zhu et al.

Summary: This study, based on American data, found that the incidence of SBM in NSCLC patients was 12.58%, with a median cancer-specific survival of 5 months; younger patients and females were more likely to develop SBM.

FUTURE ONCOLOGY (2021)

Review Genetics & Heredity

Deep learning in cancer diagnosis, prognosis and treatment selection

Khoa A. Tran et al.

Summary: Deep learning, a subdiscipline of artificial intelligence, is increasingly being applied in healthcare, particularly in cancer research. While promising results have been achieved, there are still many challenges in applying deep learning to oncology, including the need for more explainable deep learning models.

GENOME MEDICINE (2021)

Review Oncology

Predictive and Prognostic Biomarkers for Lung Cancer Bone Metastasis and Their Therapeutic Value

Xupeng Chai et al.

Summary: This review summarizes recent clinical research studies on biomarkers detected in samples obtained from patients with lung cancer bone metastasis, including various markers related to bone metabolism and their prognostic value.

FRONTIERS IN ONCOLOGY (2021)

Article Oncology

Incidence and survival outcomes of secondary liver cancer: a Surveillance Epidemiology and End Results database analysis

Zheng-Gang Wang et al.

Summary: This study characterized the epidemiology and prognostic factors of secondary liver cancer, identifying the primary site and synchronous distant metastasis as significant factors associated with patient prognosis. These findings have implications for clinical diagnosis and treatment, improving understanding of secondary liver cancer in the general population.

TRANSLATIONAL CANCER RESEARCH (2021)

Article Oncology

Identification of a high-risk group for brain metastases in non-small cell lung cancer patients

Bernardo Cacho-Diaz et al.

Summary: The study successfully identified a high-risk group of brain metastases in NSCLC patients by generating a multivariable model incorporating factors such as age, carcinoembryonic antigen levels, and mutation status. Early interventions based on this model could potentially lead to improved prognosis for these patients.

JOURNAL OF NEURO-ONCOLOGY (2021)

Review Medicine, General & Internal

Application and Performance of Artificial Intelligence Technology in Oral Cancer Diagnosis and Prediction of Prognosis: A Systematic Review

Sanjeev B. Khanagar et al.

Summary: This paper reports on the application and performance of artificial intelligence (AI) in diagnosing and predicting the occurrence of oral cancer (OC). The precision and accuracy of AI in diagnosis and predicting the occurrence of OC are higher than current clinical strategies and conventional statistical methods.

DIAGNOSTICS (2021)

Article Oncology

Predictors of prognosis of synchronous brain metastases in small-cell lung cancer patients

Sumanth P. Reddy et al.

CLINICAL & EXPERIMENTAL METASTASIS (2020)

Article Chemistry, Multidisciplinary

Radiomics-Based Prediction of Overall Survival in Lung Cancer Using Different Volumes-Of-Interest

Natascha Claudia D'Amico et al.

APPLIED SCIENCES-BASEL (2020)

Review Oncology

The lung microenvironment: an important regulator of tumour growth and metastasis

Nasser K. Altorki et al.

NATURE REVIEWS CANCER (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

Non-small cell lung cancer brain metastasis screening in the era of positron emission tomography-CT staging: Current practice and outcomes

Mauricio E. Diaz et al.

JOURNAL OF MEDICAL IMAGING AND RADIATION ONCOLOGY (2018)

Editorial Material Radiology, Nuclear Medicine & Medical Imaging

Should we screen for brain metastases in non-small cell lung cancer?

Shalini K. Vinod

JOURNAL OF MEDICAL IMAGING AND RADIATION ONCOLOGY (2018)

Editorial Material Respiratory System

Brain imaging in early stage non-small cell lung cancer: still a controversial topic?

Janna J. A. O. Schoenmaekers et al.

JOURNAL OF THORACIC DISEASE (2018)

Article Multidisciplinary Sciences

A radiomic approach for adaptive radiotherapy in non-small cell lung cancer patients

Sara Ramella et al.

PLOS ONE (2018)

Article Oncology

Cancer Statistics, 2017

Rebecca L. Siegel et al.

CA-A CANCER JOURNAL FOR CLINICIANS (2017)

Review Oncology

Lung cancer and metastasis: new opportunities and challenges

Xiangdong Wang et al.

CANCER AND METASTASIS REVIEWS (2015)

Article Radiology, Nuclear Medicine & Medical Imaging

Brain imaging in lung cancer patients without symptoms of brain metastases: a national survey of current practice in England

B. J. Hudson et al.

CLINICAL RADIOLOGY (2015)

Review Biochemistry & Molecular Biology

Machine learning applications in cancer prognosis and prediction

Konstantina Kourou et al.

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL (2015)

Article Oncology

Specific organ metastases and survival in metastatic non-small-cell lung cancer

Tomohiro Tamura et al.

MOLECULAR AND CLINICAL ONCOLOGY (2015)

Review Urology & Nephrology

Artificial neural networks and prostate cancer-tools for diagnosis and management

Xinhai Hu et al.

NATURE REVIEWS UROLOGY (2013)

Article Oncology

Specific organ metastases and survival in small cell lung cancer

Kensuke Nakazawa et al.

ONCOLOGY LETTERS (2012)

Article Pharmacology & Pharmacy

Applications of Artificial Neural Networks in Medical Science

Jigneshkumar L. Patel et al.

CURRENT CLINICAL PHARMACOLOGY (2007)

Article Oncology

Small cell lung cancer

G Rosti et al.

ANNALS OF ONCOLOGY (2006)