Oncology/Hematology

Clinical Efficacy of Real-Time Artificial Intelligence-Assisted Colonoscopy in Colorectal Polyp Detection: A Prospective Multicenter Randomized Controlled Trial.

BACKGROUND/AIMS: Early detection and removal of colon polyps are critical for preventing colorectal cancer. Computer-aided detection (CADe) systems have been introduced to increase the polyp detection rate (PDR) during colonoscopy, potentially enhancing its effectiveness. This study aimed to evaluate the efficacy of a CADe system in colorectal neoplasm detection. METHODS: This prospective, randomi...

Feasibility of transperineal prostate biopsy guided by fusion of [18F]F-PSMA-1007 PET/MRI with real-time transrectal ultrasound. Prostate cancer classification using imaging biomarkers and radiomics in PIRADS 3 lesions.

OBJECTIVE: To assess the diagnostic feasibility of transperineal biopsy guided by fusion of PET/MRI with [18F]F-PSMA-1007 and real-time transrectal ultrasound (BP PET/MR PSMA + TRUS) in patients with PIRADS 3 lesions. To analyze imaging biomarkers and radiomic features for differentiating between patients with negative biopsy, clinically non-significant prostate cancer (cnsPCa), and clinically sig...

Trajectories of affective disorders-the central structures of CRC/TRR 393.

The recurrent and often unpredictable course of affective disorders poses a critical challenge for long-term patient care. The CRC/TRR 393 consortium ...

Deep Learning Model for Differentiating Between Neoplastic Pathologic Fracture and Nonpathologic Fracture Using Hip Radiographs.

BACKGROUND: Although radiographs are the first-line imaging modality, differentiating between neoplastic pathologic fractures and nonpathologic fractu...

An accurate, straightforward computer vision algorithm for optimal tumor-feeding visualization in cone-beam computed tomography hepatic arteriography: A preliminary study.

AIM: Although standardized 3D volume rendering techniques (VRT) and embolization guidance visualize and identify tumor-feeding arteries, current vesse...

Blast cell segmentation and leukemia classification using hybrid Deep Kronecker WideResNet using blood smear images.

Acute Lymphoblastic Leukemia (ALL) is a dangerous form of leukemia, which disturbs the bone marrow and irregular White Blood Cells (WBC) for the perso...

MRI-Based Radiomics Model for Classifying Axillary Lymph Node Burden and Disease-Free Survival in Patients With Early-Stage Breast Cancer.

BACKGROUND: Axillary lymph node (ALN) burden is a key prognostic determinant in breast cancer and plays an important role in diagnosis and treatment p...

Context-aware heterogeneous graph neural network for multi-level description and invasiveness prediction in renal cell carcinoma.

The invasiveness prediction in renal cell carcinoma (RCC) is of significant importance for the decision of clinical surgical plans and the patients' p...

Hereditary syndromes and RCC: what radiologists need to know.

Hereditary renal cell carcinoma (RCC) accounts for approximately 5-8% of all renal cancers. This review provides a comprehensive overview of the seven...

Development and validation of a personalized web-based calculator of aggressive recurrence after surgery for early-stage hepatocellular carcinoma by machine learning.

BACKGROUND: Aggressive recurrence (AR) is an important factor affecting prognosis after surgery for hepatocellular carcinoma (HCC). This study aimed t...

Early prediction of response to ADT plus ARPIs in mHSPC using interpretable machine learning on PSMA PET/CT: a real-world study.

BACKGROUND: Reliable tools for early prediction of treatment response to androgen deprivation therapy (ADT) plus novel androgen receptor pathway inhib...

Functional profiling of the chaperone systems interactome in breast cancer using experimental and machine-learning data.

Breast cancer heterogeneity stems from diverse molecular alterations, including proteostasis loss due to chaperone system dysfunction. However, the im...

Lymph Node Invasion Prediction in Prostate Cancer: A Comparative Machine-Learning Study.

BACKGROUND: Accurate preoperative prediction of lymph node invasion (LNI) in prostate cancer is critical for guiding lymph node dissection. Current no...

Assessing the Accuracy of Large Language Models on European Guidelines for Cervical Cancer: An In Silico Benchmarking Study.

OBJECTIVE: Although large language models are increasingly used in clinical and research settings, the validity of the information they provide remain...

AI-assisted literature screening: A hybrid approach using large language models and retrieval-augmented generation.

OBJECTIVE: Current systematic literature reviews largely rely on manual screening of articles retrieved through keyword search, which is time-consumin...

Mass spectrometry imaging tutorial: From cancer biomarker discovery to clinical applications.

Mass spectrometry (MS), particularly mass spectrometry imaging (MSI), is an important analytical technique that facilitates the detection and spatial ...

Deciphering the role of angiogenesis in glioblastoma: Integrative insights from transcriptomic profiling, single-cell sequencing and interpretable machine learning approaches.

Glioblastoma (GBM), a highly vascularized and aggressive primary brain tumor, presents unresolved questions regarding the functional significance of a...

Artificial intelligence for TNM staging in NSCLC: a critical appraisal of segmentation utility in [1⁸F]FDG PET/CT.

PURPOSE: This study aims to investigate whether a diagnostic AI model can effectively support lesion detection and staging in non-small cell lung canc...

Explainable artificial intelligence for multi-modal cancer analysis: From genomics to immunology.

Cancer remains one of the most biologically intricate and heterogeneous diseases, with variability spanning genetic, epigenetic, metabolic, spatial, a...

Screening tools and strategies for early detection of oral cancer and potentially malignant disorders in rural and low-resource populations: A systematic review.

Oral cancer and its precursor lesions, known as oral potentially malignant disorders (OPMDs), present significant public health challenges due to high...