Chemotherapy

Performing the HINTS-exam using a mixed-reality head-mounted display in patients with acute vestibular syndrome: a feasibility study.

BACKGROUND: In patients with acute vestibular syndrome (AVS) differentiating between benign acute peripheral vestibular disorders and possible life-threatening central, causes such as stroke, can be challenging due to similar symptoms. AVS patients experience dizziness, vertigo, imbalance, nausea, vomiting, and abnormal eye movements. This research evaluates the feasibility of using the eye-tracki...

Comparative analysis of multi-zone peritumoral radiomics in breast cancer for predicting NAC response using ABVS-based deep learning models.

BACKGROUND: Peritumoral characteristics demonstrate significant predictive value for neoadjuvant chemotherapy (NAC) response in breast cancer (BC) through tumor-stromal interactions. Radiomics analysis of peritumoral regions has shown robust capability in predicting treatment outcomes; however, the optimal peritumoral thickness for maximizing predictive accuracy remains undefined.

Prediction of induction chemotherapy efficacy in patients with locally advanced nasopharyngeal carcinoma using habitat subregions derived from multi-modal MRI radiomics.

OBJECTIVE: This study aims to predict the early efficacy of induction chemotherapy (ICT) in patients with locally advanced nasopharyngeal carcinoma (L...

Microbiota as diagnostic biomarkers: advancing early cancer detection and personalized therapeutic approaches through microbiome profiling.

The important function of microbiota as therapeutic modulators and diagnostic biomarkers in cancer has been shown by recent developments in microbiome...

Preoperative kidney tumor risk estimation with AI: From logistic regression to transformer.

We consider the problem of renal mass risk classification to support doctors in adjuvant treatment decisions following nephrectomy. Recommendation of ...

Artificial intelligence can help individualize Wilms tumor treatment by predicting tumor response to preoperative chemotherapy.

PURPOSE: To create a computer-aided prediction (CAP) system to predict Wilms tumor (WT) responsiveness to preoperative chemotherapy (PC) using pre-the...

Single and Multi-Objective Optimization of the Red Pine Mushroom Lactarius deliciosus (Agaricomycetes) Extraction Conditions Using Artificial Intelligence Methods and Biological Activities of Optimized Extracts.

In this study, the biological activities of Lactarius deliciosus were determined. Experimental studies were carried out using a soxhlet device, in the...

Ensemble learning guided survival prediction and chemotherapy benefit analysis in high-grade chondrosarcoma: A study based on the surveillance, epidemiology, and end results (SEER) database.

The chemotherapy benefit for high-grade chondrosarcoma remains controversial. Ensemble learning has better overall performance than single computatio...

Predicting neoadjuvant chemotherapy response in locally advanced gastric cancer using a machine learning model combining radiomics and clinical biomarkers.

RATIONALE AND OBJECTIVES: Neoadjuvant chemotherapy (NAC) is a promising therapeutic strategy for managing locally advanced gastric cancer (LAGC), aimi...

Monitoring Over Time of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Patients Through an Ensemble Vision Transformers-Based Model.

BACKGROUND: Morphological and vascular characteristics of breast cancer can change during neoadjuvant chemotherapy (NAC). Dynamic contrast-enhanced ma...

Explainable Machine Learning Predictions for the Benefit From Chemotherapy in Advanced Non-Small Cell Lung Cancer Without Available Targeted Mutations.

BACKGROUND: Non-small cell lung cancer (NSCLC) is a global health challenge. Chemotherapy remains the standard therapy for advanced NSCLC without muta...

NACNet: A Histology Context-aware Transformer Graph Convolution Network for Predicting Treatment Response to Neoadjuvant Chemotherapy in Triple Negative Breast Cancer

Neoadjuvant chemotherapy (NAC) response prediction for triple negative breast cancer (TNBC) patients is a challenging task clinically as it requires...

[Applications of artificial intelligence for imaging-driven diagnosis and treatment of bone and soft tissue tumors].

Bone and soft tissue tumors occur in the musculoskeletal system, and malignant bone tumors of bone and soft tissue account for 0.2% of all human malig...

Tailoring nonsurgical therapy for elderly patients with head and neck squamous cell carcinoma: A deep learning-based approach.

To assess deep learning models for personalized chemotherapy selection and quantify the impact of baseline characteristics on treatment efficacy for e...

Development and validation of machine learning models for predicting HER2-zero and HER2-low breast cancers.

OBJECTIVES: To develop and validate machine learning models for human epidermal growth factor receptor 2 (HER2)-zero and HER2-low using MRI features p...

Tailored chemotherapy: Innovative deep-learning model customizing chemotherapy for high-grade serous ovarian carcinoma.

Identification of diagnostic biomarkers and immune cell profiles associated with COPD integrated bioinformatics and machine learning.

This retrospective transcriptomic study leveraged bioinformatics and machine learning algorithms to identify novel gene biomarkers and explore immune ...

Coalitions of AI-based Methods Predict 15-Year Risks of Breast Cancer Metastasis Using Real-World Clinical Data with AUC up to 0.9

Breast cancer is one of the two cancers responsible for the most deaths in women, with about 42,000 deaths each year in the US. That there are over ...

Natural Language Processing Accurately Differentiates Cancer Symptom Information in Electronic Health Record Narratives.

PURPOSE: Identifying cancer symptoms in electronic health record (EHR) narratives is feasible with natural language processing (NLP). However, more ef...

Predicting tumor mutation burden and VHL mutation from renal cancer pathology slides with self-supervised deep learning.

BACKGROUND: Tumor mutation burden (TMB) and VHL mutation play a crucial role in the management of patients with clear cell renal cell carcinoma (ccRCC...