Other Cancers

Advances in melanoma immunotherapy: harnessing vaccination as a potential novel immunotherapeutic strategy.

Melanoma, an aggressive form of skin cancer, demands innovative immunotherapeutic strategies to improve patient outcomes. This review explores recent advances in melanoma immunotherapy, with a particular focus on vaccination as a promising approach. It examines diverse vaccine platforms aimed at eliciting robust immune responses against melanoma-specific antigens, emphasizing the role of adjuvants...

Are we ready for amyloid-related imaging abnormalities (ARIA) monitoring? A European survey among neuroradiologists and neurologists by the ESNR/EAN Working Group.

OBJECTIVES: Amyloid-lowering immunotherapies can cause amyloid-related imaging abnormalities (ARIA), requiring brain MRI for detection and monitoring. The European Society of Neuroradiology (ESNR)/European Academy of Neurology (EAN) ARIA Working Group conducted a survey to assess European clinicians' readiness for this logistical challenge and need for further education on ARIA. MATERIALS AND METH...

Advancing patient stratification in major depressive disorder: Evaluation of clinical staging and machine learning prediction models based on real-world data.

OBJECTIVE: To evaluate the utility of a clinical staging model and compared its prognostic performance with an unsupervised machine learning-based str...

Unraveling stress-adaptation pathways in cancer: Functional dissection through CRISPR-based genetic screens.

Cancer cells face a hostile microenvironment characterized by hypoxia, nutrient deprivation, endoplasmic reticulum (ER) stress, and oxidative imbalanc...

Integration of histopathological characteristics by machine learning improves the prediction of neoadjuvant immunochemotherapy response in triple-negative breast cancer.

Neoadjuvant immunochemotherapy (NAIC) is a standard treatment for triple-negative breast cancer (TNBC), but there is no reliable biomarker to identify...

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): outcome prediction with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults and present ongoing challenges in clinical management, particularl...

Automated CT-derived body composition predicts pathologic response to neoadjuvant immunotherapy in non-small cell lung cancer.

Tumor-intrinsic biomarkers alone insufficiently predict pathological complete response (pCR) to neoadjuvant immunochemotherapy (NICT) in non-small cel...

[Chronic skin damage from UV radiation].

Ultraviolet (UV) radiation is the primary risk factor for the development of both melanocytic and nonmelanocytic skin cancer. In particular, UVA and U...

Single‑cell mapping of neutrophil extracellular trap signatures in lung adenocarcinoma reveals immune landscapes, prognostic potential, and therapeutic targets.

Neutrophil extracellular traps (NETs) have emerged as key modulators in the tumor microenvironment, yet their cellular heterogeneity, molecular mechan...

Artificial intelligence for personalized management of vestibular schwannoma: a multidisciplinary clinical implementation study.

OBJECTIVES: Management of patients with vestibular schwannoma (VS) relies on precise tumor size and growth trend evaluation. We introduce and evaluate...

Single-cell and machine learning-based analysis of the molecular mechanism of Banxia Xiexin Decoction in the treatment of gastric cancer.

UNLABELLED: Gastric cancer (GC) is one of the most common malignant tumors worldwide. Banxia Xiexin Decoction (BXXXD) has a significant therapeutic ef...

From bench to bedside: The clinical relevance of atrial electrical remodeling in atrial fibrillation therapy.

Atrial electrical remodeling spans molecular, electrical, and structural alterations that shorten refractoriness, facilitate reentry, and ultimately c...

Identifying transcriptional signatures of leukocytes in tissue and blood for multicancer diagnosis by using machine learning methods.

Investigating the transcriptional signatures of immune cells in various cancer types is crucial for understanding their roles in the tumor microenviro...

Magnetically Driven Lasing Microrobots for Precise Photodynamic Therapy.

Photodynamic therapy (PDT) is an emerging approach for tumor treatment, valued for its noninvasive and stimuli-responsive properties. However, its the...

Classification of Salivary Gland Tumors on Ultrasound Using Artificial Intelligence: A Systematic Review and Meta-Analysis.

OBJECTIVE: Accurate classification of salivary gland tumors is critical to guiding appropriate management. This study evaluates the diagnostic perform...

Minimally Invasive, Label-Free, Point-of-Care Histopathological Diagnostic Platform of Malignant Tumors of the Female Reproductive System Based on Raman Spectroscopy and Machine Learning.

Fast intraoperative histopathology is critical for optimal surgery in ovarian, endometrial and cervical cancers, yet frozen-section pathology is slow ...

Liver cancer segmentator: Metadata-guided confidence scoring for reliable segmentation of colorectal liver metastases in CT.

BACKGROUND AND OBJECTIVE: This study introduces the liver cancer segmentator (LCS), a deep learning model designed for automatic and robust segmentati...

Deep learning image reconstruction improves 40 keV virtual monoenergetic image quality in rectal cancer.

BACKGROUND: Accurate preoperative evaluation of rectal cancer is essential for staging and treatment planning. Low-energy virtual monoenergetic imagin...

A droplet digital LAMP-based lab-on-a-disc system for multiplex allele-specific detection of tumor-derived DNA mutations.

The absence of accurate, rapid, fully automated, and cost-effective detection methods has hindered the clinical translation of tumor-derived DNA mutat...

Artificial intelligence in diagnostic, prognostic, and predictive genomic biomarkers for prostate cancer: Ready for prime time?

INTRODUCTION: Until recently, the widespread use of genetic markers in prostate cancer (PCa) has been limited by the complexities and cost of genomic ...