AIMC Topic: Female

Clear Filters Showing 81 to 90 of 26394 articles

18F-FDG PET/CT-based deep radiomic models for enhancing chemotherapy response prediction in breast cancer.

Medical oncology (Northwood, London, England)
Enhancing the accuracy of tumor response predictions enables the development of tailored therapeutic strategies for patients with breast cancer. In this study, we developed deep radiomic models to enhance the prediction of chemotherapy response after...

Multimodal anti fraud education improves cognitive emotional and behavioral engagement in older adults.

Scientific reports
This study examines the differential effectiveness of video-based versus text-based anti-fraud educational interventions in improving cognitive comprehension, emotional engagement, and behavioral intentions among older adults. Using a stratified samp...

AI microscope facilitates accurate interpretation of HER2 immunohistochemical scores 0 and 1+ in invasive breast cancer.

Scientific reports
Accurate interpretation of human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) scores 0 and 1+ is crucial for treating HER2-low breast cancer patients with antibody-drug conjugates. To improve diagnostic precision, we developed...

AI-driven fusion of multimodal data for Alzheimer's disease biomarker assessment.

Nature communications
Alzheimer's disease (AD) diagnosis hinges on detecting amyloid beta (Aβ) plaques and neurofibrillary tau (τ) tangles, typically assessed using PET imaging. While accurate, these modalities are expensive and not widely accessible, limiting their utili...

Construction and validation of a urinary stone composition prediction model based on machine learning.

Urolithiasis
The composition of urinary calculi serves as a critical determinant for personalized surgical strategies; however, such compositional data are often unavailable preoperatively. This study aims to develop a machine learning-based preoperative predicti...

Deep learning and radiomics fusion for predicting the invasiveness of lung adenocarcinoma within ground glass nodules.

Scientific reports
Microinvasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) require distinct treatment strategies and are associated with different prognoses, underscoring the importance of accurate differentiation. This study aims to develop a predictive m...

Enhancing meningioma tumor classification accuracy through multi-task learning approach and image analysis of MRI images.

PloS one
BACKGROUND: Accurate classification of meningioma brain tumors is crucial for determining the appropriate treatment plan and improving patient outcomes. However, this task is challenging due to the slow-growing nature of these tumors and the potentia...

Improving early detection of Alzheimer's disease through MRI slice selection and deep learning techniques.

Scientific reports
Alzheimer's disease is a progressive neurodegenerative disorder marked by cognitive decline, memory loss, and behavioral changes. Early diagnosis, particularly identifying Early Mild Cognitive Impairment (EMCI), is vital for managing the disease and ...

Prediction of cervical cancer lymph node metastasis based on multisequence magnetic resonance imaging radiomics and deep learning features: a dual-center study.

Scientific reports
Cervical cancer is a leading cause of death from malignant tumors in women, and accurate evaluation of occult lymph node metastasis (OLNM) is crucial for optimal treatment. This study aimed to develop several predictive models-including Clinical mode...

Development and validation of a machine learning model for predicting vulnerable carotid plaques using routine blood biomarkers and derived indicators: insights into sex-related risk patterns.

Cardiovascular diabetology
BACKGROUND: Early detection of vulnerable carotid plaques is critical for stroke prevention. This study aimed to develop a machine learning model based on routine blood tests and derived indices to predict plaque vulnerability and assess sex-specific...