AIMC Topic: Middle Aged

Clear Filters Showing 3751 to 3760 of 17155 articles

Deep learning classification of MGMT status of glioblastomas using multiparametric MRI with a novel domain knowledge augmented mask fusion approach.

Scientific reports
We aimed to build a robust classifier for the MGMT methylation status of glioblastoma in multiparametric MRI. We focused on multi-habitat deep image descriptors as our basic focus. A subset of the BRATS 2021 MGMT methylation dataset containing both M...

Detecting noncredible symptomology in ADHD evaluations using machine learning.

Journal of clinical and experimental neuropsychology
INTRODUCTION: Diagnostic evaluations for attention-deficit/hyperactivity disorder (ADHD) are becoming increasingly complicated by the number of adults who fabricate or exaggerate symptoms. Novel methods are needed to improve the assessment process re...

Risk score stratification of cutaneous melanoma patients based on whole slide images analysis by deep learning.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: There is a need to improve risk stratification of primary cutaneous melanomas to better guide adjuvant therapy. Taking into account that haematoxylin and eosin (HE)-stained tumour tissue contains a huge amount of clinically unexploited mo...

Machine-learning model based on ultrasomics for non-invasive evaluation of fibrosis in IgA nephropathy.

European radiology
OBJECTIVES: To develop and validate an ultrasomics-based machine-learning (ML) model for non-invasive assessment of interstitial fibrosis and tubular atrophy (IF/TA) in patients with IgA nephropathy (IgAN).

A radiomics model combining machine learning and neural networks for high-accuracy prediction of cervical lymph node metastasis on ultrasound of head and neck squamous cell carcinoma.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: This study aimed to develop an ultrasound image-based radiomics model for diagnosing cervical lymph node (LN) metastasis in patients with head and neck squamous cell carcinoma (HNSCC) that shows higher accuracy than previous models.

A Comparison of Prostate Cancer Screening Information Quality on Standard and Advanced Versions of ChatGPT, Google Gemini, and Microsoft Copilot: A Cross-Sectional Study.

American journal of health promotion : AJHP
PurposeArtificially Intelligent (AI) chatbots have the potential to produce information to support shared prostate cancer (PrCA) decision-making. Therefore, our purpose was to evaluate and compare the accuracy, completeness, readability, and credibil...

Forensic sex classification by convolutional neural network approach by VGG16 model: accuracy, precision and sensitivity.

International journal of legal medicine
INTRODUCTION: In the reconstructive phase of medico-legal human identification, the sex estimation is crucial in the reconstruction of the biological profile and can be applied both in identifying victims of mass disasters and in the autopsy room. Du...

Development of a Clinically Applicable Deep Learning System Based on Sparse Training Data to Accurately Detect Acute Intracranial Hemorrhage from Non-enhanced Head Computed Tomography.

Neurologia medico-chirurgica
Non-enhanced head computed tomography is widely used for patients presenting with head trauma or stroke, given acute intracranial hemorrhage significantly influences clinical decision-making. This study aimed to develop a deep learning algorithm, ref...

Machine learning-based algorithm of drug-resistant prediction in newly diagnosed patients with temporal lobe epilepsy.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVES: To develop a predicted algorithm for drug-resistant epilepsy (DRE) in newly diagnosed temporal lobe epilepsy (TLE) patients.

Detecting B-cell lymphoma-6 overexpression status in primary central nervous system lymphoma using multiparametric MRI-based machine learning.

Neuroradiology
PURPOSE: In primary central nervous system lymphoma (PCNSL), B-cell lymphoma-6 (BCL-6) is an unfavorable prognostic biomarker. We aim to non-invasively detect BCL-6 overexpression in PCNSL patients using multiparametric MRI and machine learning techn...