Other Cancers

Nodular Growths of NF2 -Related Schwannomatosis Vestibular Schwannoma: Clinical and Therapeutical Consequences.

BACKGROUND AND OBJECTIVES: Neurofibromatosis type 2-related schwannomatosis ( NF2 -SWN) is marked by the growth of bilateral vestibular schwannoma (VS). VS size and tumor growth rate are not correlated with hearing modifications, making a hearing preservation strategy uncertain. The goal of this study was to identify the volumetric growth of VS in NF2 -SWN using a specific 3-dimensional (3D) volum...

Development and validation of a nomogram combining PI-RADS v2.1 and clinical indicators for the diagnosis of prostate cancer in patients with PSA ≤ 20 ng/mL.

PURPOSE: This investigation focused on developing a predictive clinical tool that combines biparametric MRI-derived PI-RADS v2.1 assessments with patient-specific biomarkers. The model was designed to optimize prostate cancer detection reliability in individuals exhibiting prostate-specific antigen concentrations below 20 ng/mL, particularly targeting the diagnostic challenges presented by this in...

Home-Based Pain Management in Palliative Care in the Context of Artificial Intelligence.

Breaking the bottleneck of asthma treatment: the future of omni-targeted therapy.

BACKGROUND: Bronchial asthma is a complex, highly heterogeneous disease involving multiple pathological mechanisms and inflammatory pathways. Traditio...

Comparative analysis of convolutional neural network models for the histopathological differentiation of acinic cell carcinoma and secretory carcinoma.

OBJECTIVE: Although artificial intelligence tools show promise for enhancing the diagnosis of head and neck lesions, few studies have tested these res...

Predicting sentinel lymph node metastasis in melanoma patients: A machine learning-based predictive model.

BACKGROUND: Risk factors for sentinel lymph node (SLN) metastasis in melanoma have been studied. However, there remains a lack of widely applicable mo...

Consensus position statements for the standardized application of histological grading and staging systems in MASH clinical trials.

BACKGROUND & AIMS: Assessment of histologic disease activity (grading) and fibrosis (staging) is a prerequisite for patient selection and evaluation o...

Artificial intelligence predicts c-KIT exon 11 genotype by phenotype in canine cutaneous mast cell tumors: Can human observers learn it?

Canine cutaneous mast cell tumors (ccMCTs) are frequent neoplasms with variable biological behaviors. Internal tandem duplication mutations in c-KIT e...

Genomic and Transcriptomic Profiling of High-risk Bladder Cancer Reveals Diverse Molecular and Microenvironment Ecosystems.

BACKGROUND AND OBJECTIVE: High-risk bladder cancer recurs in 30% of cases and causes fatal outcomes in 10% within 2 yr despite surgical resection, end...

Tumoral Skin Invasion Is an Independent Predictor of Rapid Recurrence in Head and Neck Cancer.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is an aggressive malignancy, with 50% of patients recurring. A subset of patients experience...

Automated detection and characterization of small cell lung cancer liver metastasis on computed tomography.

PURPOSE: Small cell lung cancer (SCLC) is an aggressive disease with diverse phenotypes that reflect the heterogeneous expression of tumor-related gen...

Detection of Lymph Node Metastasis in Thyroid Cancer Using Deep Learning and Second Harmonic Generation Imaging.

Papillary thyroid carcinoma (PTC) is the most prevalent type of thyroid cancer, with a significant proportion of patients being susceptible to lymph n...

Development and Validation of a Novel Plasma Metabolomic Signature for the Detection of Renal Cell Carcinoma.

BACKGROUND AND OBJECTIVE: Early diagnosis is critical for improving survival in renal cell carcinoma (RCC); yet, effective laboratory tests remain lac...

Dual-feature cross-fusion network for precise brain tumor classification: a neurocomputational approach.

Brain tumors represent a significant neurological challenge, affecting individuals across all age groups. Accurate and timely diagnosis of tumor types...

Microbiome-transcriptome-histology triad enhances survival risk stratification in multiple cancers.

Accurate prognostic stratification is essential for optimizing postoperative therapeutic strategies in oncology. While deep learning approaches have s...

A systematic review on deep learning based brain tumor segmentation and detection using MRI: Past insights, present techniques and future trends.

The abnormal growth of cells leads to brain malignancy in humans, which is among the most prevalent causes of fatalities in adults worldwide. Patients...

Role of NNMT and NM23A for diagnosis of RCC: Renal Cell Carcinoma.

OBJECTIVE: This study investigates the diagnostic potential of nicotinamide N-methyltransferase (NNMT) and NM23A as biomarkers for renal cell carcinom...

A deep learning method for diagnosis of oral potentially malignant disorders.

OBJECTIVES: This study aimed to develop and validate a two-stage deep learning method for diagnosing oral potentially malignant disorders (OPMDs). We ...

Liquid biopsy based on multi-targeted capture of urinary tumor DNA combined with machine learning to detect urothelial carcinoma: a multicenter prospective study.

PURPOSE: Diagnostics for urothelial carcinoma have low sensitivity, thereby negatively impacting diagnostic outcomes. Herein, we present BiovueUro, a ...

Radiomics-based artificial intelligence (AI) models in colorectal cancer (CRC) diagnosis, metastasis detection, prognosis, and treatment response prediction.

Colorectal cancer (CRC) is the third most common cause of cancer-related morbidity and mortality in the world. Radiomics and radiogenomics are utilize...