Related references
Note: Only part of the references are listed.An Online Prognostic Application for Melanoma Based on Machine Learning and Statistics
Wenhui Liu et al.
JOURNAL OF PLASTIC RECONSTRUCTIVE AND AESTHETIC SURGERY (2022)
Clinical performance indicators for monitoring the management of cutaneous melanoma: a population-based perspective
Alessandra Buja et al.
MELANOMA RESEARCH (2022)
Application of Deep Learning on the Prognosis of Cutaneous Melanoma Based on Full Scan Pathology Images
Anhai Li et al.
BIOMED RESEARCH INTERNATIONAL (2022)
A deep learning model based on whole slide images to predict disease-free survival in cutaneous melanoma patients
Maria Colomba Comes et al.
SCIENTIFIC REPORTS (2022)
Cutaneous Melanoma in Alpine Population: Incidence Trends and Clinicopathological Profile
Alessandra Buja et al.
CURRENT ONCOLOGY (2022)
Prognostic factors and population-based analysis of melanoma with sentinel lymph node biopsy
Ping-Chung Wu et al.
SCIENTIFIC REPORTS (2021)
Bioinformatic and Machine Learning Applications in Melanoma Risk Assessment and Prognosis: A Literature Review
Emily Z. Ma et al.
GENES (2021)
Pyroptosis-Related Gene Signatures Can Robustly Diagnose Skin Cutaneous Melanoma and Predict the Prognosis
Anji Ju et al.
FRONTIERS IN ONCOLOGY (2021)
Data Quality, Data Sharing, and Moving Artificial Intelligence Forward
Joann G. Elmore et al.
JAMA NETWORK OPEN (2021)
Histopathologic classification and prognostic factors of melanoma: a 2021 update
Mattheos Bobos
ITALIAN JOURNAL OF DERMATOLOGY AND VENEREOLOGY (2021)
The use of artificial intelligence, machine learning and deep learning in oncologic histopathology
Ahmed S. Sultan et al.
JOURNAL OF ORAL PATHOLOGY & MEDICINE (2020)
Emerging role of deep learning-based artificial intelligence in tumor pathology
Yahui Jiang et al.
CANCER COMMUNICATIONS (2020)
Deep learning-level melanoma detection by interpretable machine learning and imaging biomarker cues
Daniel S. Gareau et al.
JOURNAL OF BIOMEDICAL OPTICS (2020)
Risk prediction in cutaneous melanoma patients from their clinico-pathological features: superiority of clinical data over gene expression data
Chakit Arora et al.
HELIYON (2020)
Introduction to artificial intelligence in medicine
Yoav Mintz et al.
MINIMALLY INVASIVE THERAPY & ALLIED TECHNOLOGIES (2019)
Applications of Machine Learning in Real-Life Digital Health Interventions: Review of the Literature
Andreas K. Triantafyllidis et al.
JOURNAL OF MEDICAL INTERNET RESEARCH (2019)
Efficient learning from big data for cancer risk modeling: A case study with melanoma
Aaron N. Richter et al.
COMPUTERS IN BIOLOGY AND MEDICINE (2019)
A nomogram for predicting survival in patients with nodular melanoma A population-based study
Jin Yang et al.
MEDICINE (2019)
Artificial intelligence: Implications for the future of work
John Howard
AMERICAN JOURNAL OF INDUSTRIAL MEDICINE (2019)
Current state of melanoma diagnosis and treatment
Lauren E. Davis et al.
CANCER BIOLOGY & THERAPY (2019)
Impact of American Joint Committee on Cancer 8th edition classification on staging and survival of patients with melanoma
Theodora Kanaki et al.
EUROPEAN JOURNAL OF CANCER (2019)
The eighth edition American Joint Committee on Cancer (AJCC) melanoma staging system: implications for melanoma treatment and care
Emily Z. Keung et al.
EXPERT REVIEW OF ANTICANCER THERAPY (2018)
Machine learning and melanoma: The future of screening
Tyler Safran et al.
JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY (2018)
Malignant Melanoma: Beyond the Basics
Sabrina N. Pavri et al.
PLASTIC AND RECONSTRUCTIVE SURGERY (2016)
Current Staging and Prognostic Factors in Melanoma
Edmund K. Bartlett et al.
SURGICAL ONCOLOGY CLINICS OF NORTH AMERICA (2015)
Cutaneous Malignant Melanoma: Update on Diagnostic and Prognostic Biomarkers
Ossama Abbas et al.
AMERICAN JOURNAL OF DERMATOPATHOLOGY (2014)
Prognostic factors in melanoma
Witold Kycler et al.
REPORTS OF PRACTICAL ONCOLOGY AND RADIOTHERAPY (2006)
A nomogram that predicts the presence of sentinel node metastasis in melanoma with better discrimination than the American Joint Committee on Cancer staging system
SL Wong et al.
ANNALS OF SURGICAL ONCOLOGY (2005)
On the relationship between classical grid search and probabilistic roadmaps
SM LaValle et al.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH (2004)