PURPOSE There is a need for an improved understanding of clinical and biologic risk
factors in pediatric cancer to improve patient outcomes. Machine learning (ML) represents …

Background Brain metastasis (BM) is a serious neurological complication of cancer of
different origins. The value of deep learning (DL) to identify multiple types of primary origins …

Parkinson's disease is caused due to the progressive loss of dopaminergic neurons in the
substantia nigra pars compacta (SNc). Presently, with the exponential growth of the aging …

Fractal and grey level co-occurrence matrix (GLCM) analysis represent two mathematical
computer-assisted algorithms that are today thought to be able to accurately detect and …

Background Stereotactic irradiation is widely used in brain oligo-metastases treatment. The
aim of this study is to evaluate the prognostic value of magnetic resonance imaging (MRI) …

Objective To develop and validate a machine learning (ML) approach for automatic three-
dimensional (3D) histopathological grading of osteochondral samples imaged with contrast …

A novel hybrid approach for the identification of brain regions using magnetic resonance
images accountable for brain tumor is presented in this paper. Classification of medical …

Purpose MR‐imaging hallmarks of glioblastoma (GB), cerebral lymphoma (CL), and
demyelinating lesions are gadolinium (Gd) uptake due to blood–brain barrier disruption …

Despite previous research efforts in the fields of histology and cell physiology, the
relationship between chromatin structural organization and nuclear shape remains unclear …

The image analysis of the brain with machine learning continues to be a relevant work for
the detection of different characteristics of this complex organ. Recent research has …