Breast Cancer

Developing and Validating a Prediction Model for the Severe Pain-Fatigue-Sleep Disturbance Symptom Cluster in Patients with Lung Cancer Following Chemotherapy: A Machine Learning Analysis.

OBJECTIVES: Pain-fatigue-sleep disturbance symptom (PFS) cluster is the most common symptom cluster in patients with lung cancer following chemotherapy, which significantly impacts their quality of life. This study aims to develop and validate a machine learning-based prediction model for the severe PFS cluster and identify the relevant factors in patients with lung cancer following chemotherapy. ...

Precision treatment with artificial intelligence assisted subtyping enhances therapeutic efficacy in HR+/HER2- breast cancer: The LINUXtrial.

We report the results of LINUX (NCT05594095), a multicenter, randomized, controlled phase II platform trial aiming to identify effective precision treatments for hormone receptor-positive/human epidermal growth factor receptor 2-negative metastatic breast cancer after resistance to cyclin-dependent kinase 4/6 inhibitor. A total of 105 patients were categorized into four similarity network fusion (...

Application of machine learning to create a prediction model for the need of aggressive nutritional intervention during head & neck cancer radiotherapy.

BACKGROUND: Curative-intent radiotherapy (RT) or chemoradiotherapy (CRT) for head and neck squamous cell carcinoma (HNSCC) frequently leads to mucosit...

3D Automated Segmentation of Bronchial Abnormalities on Ultrashort Echo Time MRI: A Quantitative MR Outcome in Cystic Fibrosis.

BACKGROUND: Cystic fibrosis (CF) monitoring relies on computed tomography (CT), but ultra-short echo time MRI (UTE-MRI) offers a radiation-free altern...

Three-dimensional surface scanning for registration in stereotactic neurosurgery: a cadaveric feasibility study.

OBJECTIVE: Achieving submillimetric accuracy in stereotactic neurosurgery remains critical for safely targeting deep brain structures. Current workflo...

Molecular targeted therapies, omics, and AI based theranostics approaches for the treatment of prostate cancer.

Cancer is a disease that begins with genetic and epigenetic alterations occurring in specific cells, some of which can spread and migrate to other tis...

A Comparative, Multiobserver Analysis of Nodal Contouring Methods in Pelvic Online Cone Beam-Based Adaptive Radiation Therapy.

PURPOSE: In online cone beam computed tomography (CBCT)-based adaptive radiation therapy (ART), nodal recontouring ensures sufficient nodal coverage b...

Accuracy of Photon Dose Calculation on Photon-Counting Computed Tomography-A Comparison Study Based on Virtual Monoenergetic and Electron Density (Rho) Images for Pancreatic Cases.

PURPOSE: Photon-counting computed tomography (PCCT) offers versatile anatomic information because of better energy discrimination and higher spatial r...

Combined dual-phase CT radiomics and deep transfer learning model for oxaliplatin response in unresectable colorectal liver metastases.

OBJECTIVES: Accurate prediction of response to first-line oxaliplatin-based chemotherapy in unresectable colorectal liver metastases (CRLM) is critica...

HPCSMN: A Classification Method of Chemotherapy Sensitivity of Hypopharyngeal Cancer Based on Multimodal Network.

The treatment of hypopharyngeal cancer faces complex challenges, and accurate prediction of chemotherapy sensitivity is crucial for personalized treat...

Total-body [18F]FDG-PET/CT imaging of healthy volunteers with minimal effective dose.

PURPOSE: High-sensitivity, total-body (TB) positron emission tomography (PET) and computed tomography (CT) imaging systems enable substantial reductio...

Hopfield neural networks with diverse activation functions: impact of variable action gradients and electromagnetic radiation effects.

Activation functions and their variable gradient action are pivotal in bridging artificial neural networks with the dynamic behavior of biological neu...

Emerging trends in nuclear medicine: breakthrough in radiopharmaceuticals, Geant4 simulations, and AI integration.

Nuclear medicine has witnessed revolutionary progress, spurred by advances in radiopharmaceuticals, computational modeling, and artificial intelligenc...

Special AAO Report: Recommendations on Screening for Hydroxychloroquine Retinopathy (2025 Revision).

BACKGROUND: The American Academy of Ophthalmology recommendations on screening for hydroxychloroquine (HCQ) retinopathy are now a decade old. This rev...

Pathologic assessment of resected stage III non-small cell lung cancer after neoadjuvant chemotherapy: identification of additional prognostic factors.

BACKGROUND: Non-small cell lung cancer (NSCLC) patients undergoing neoadjuvant chemotherapy (NACT) followed by surgery represent an ideal clinical set...

The Impact of Radiation Dose to Bowel on the Risk of Developing Gastrointestinal Toxicities When Treating Abdominopelvic Soft-Tissue Sarcomas With Preoperative Radiation Therapy.

PURPOSE: Abdominopelvic soft-tissue sarcomas (AP-STS) are selectively treated with radiation therapy (RT) followed by surgery. We investigated dosimet...

Flavonoid-modulated JAK-STAT signaling mitigates malignant transformation and drug resistance in breast tumors: A clinically relevant 3PM-guided innovation.

BACKGROUND: Breast cancer (BC) treatment efficacy is often compromised by tumor cell plasticity and multidrug resistance of multi-factorial origin. Am...

Deep learning for accurate tumour volume measurement and prediction of therapy response in paediatric osteosarcoma.

OBJECTIVES: To assess treatment response in osteosarcoma, two automated convolutional neural networks (CNNs) were developed to quantify tumour volumes...

Enhanced prediction of breast cancer patient response to chemotherapy by integrating deconvolved expression patterns of immune, stromal and tumor cells.

The tumor microenvironment (TME) is a complex ecosystem of diverse cell types whose interactions govern tumor growth and clinical outcome. While multi...

Magnetic resonance imaging-based artificial intelligence model predicts neoadjuvant therapy response in triple-negative breast cancer.

PURPOSE: Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited treatment options and poorer overall survival tha...