Explainable artificial intelligence: a comprehensive review
Thanks to the exponential growth in computing power and vast amounts of data, artificial
intelligence (AI) has witnessed remarkable developments in recent years, enabling it to be …
intelligence (AI) has witnessed remarkable developments in recent years, enabling it to be …
Designing deep learning studies in cancer diagnostics
A Kleppe, OJ Skrede, S De Raedt, K Liestøl… - Nature Reviews …, 2021 - nature.com
The number of publications on deep learning for cancer diagnostics is rapidly increasing,
and systems are frequently claimed to perform comparable with or better than clinicians …
and systems are frequently claimed to perform comparable with or better than clinicians …
Explainable artificial intelligence (xai) on timeseries data: A survey
Most of state of the art methods applied on time series consist of deep learning methods that
are too complex to be interpreted. This lack of interpretability is a major drawback, as several …
are too complex to be interpreted. This lack of interpretability is a major drawback, as several …
Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics
YS Choi, S Bae, JH Chang, SG Kang, SH Kim… - Neuro …, 2021 - academic.oup.com
Background Glioma prognosis depends on isocitrate dehydrogenase (IDH) mutation status.
We aimed to predict the IDH status of gliomas from preoperative MR images using a fully …
We aimed to predict the IDH status of gliomas from preoperative MR images using a fully …
Emerging role of artificial intelligence in diagnosis, classification and clinical management of glioma
Glioma represents a dominant primary intracranial malignancy in the central nervous
system. Artificial intelligence that mainly includes machine learning, and deep learning …
system. Artificial intelligence that mainly includes machine learning, and deep learning …
[HTML][HTML] Quantitative MRI-based radiomics for noninvasively predicting molecular subtypes and survival in glioma patients
Gliomas can be classified into five molecular groups based on the status of IDH mutation,
1p/19q codeletion, and TERT promoter mutation, whereas they need to be obtained by …
1p/19q codeletion, and TERT promoter mutation, whereas they need to be obtained by …
[HTML][HTML] Isocitrate dehydrogenase (IDH) status prediction in histopathology images of gliomas using deep learning
Mutations in isocitrate dehydrogenase genes IDH1 and IDH2 are frequently found in diffuse
and anaplastic astrocytic and oligodendroglial tumours as well as in secondary …
and anaplastic astrocytic and oligodendroglial tumours as well as in secondary …
The 2021 WHO Classification for Gliomas and Implications on Imaging Diagnosis: Part 1—Key Points of the Fifth Edition and Summary of Imaging Findings on Adult …
YW Park, P Vollmuth, M Foltyn‐Dumitru… - Journal of Magnetic …, 2023 - Wiley Online Library
The fifth edition of the World Health Organization (WHO) classification of central nervous
system tumors published in 2021 advances the role of molecular diagnostics in the …
system tumors published in 2021 advances the role of molecular diagnostics in the …
Artificial intelligence-assisted selection and efficacy prediction of antineoplastic strategies for precision cancer therapy
ZHE Zhang, X Wei - Seminars in Cancer Biology, 2023 - Elsevier
The rapid development of artificial intelligence (AI) technologies in the context of the vast
amount of collectable data obtained from high-throughput sequencing has led to an …
amount of collectable data obtained from high-throughput sequencing has led to an …
Machine learning for the prediction of molecular markers in glioma on magnetic resonance imaging: a systematic review and meta-analysis
BACKGROUND Molecular characterization of glioma has implications for prognosis,
treatment planning, and prediction of treatment response. Current histopathology is limited …
treatment planning, and prediction of treatment response. Current histopathology is limited …