Other Cancers

Pretreatment multiparametric MRI-based habitat radiomics and 2.5D deep learning for predicting early complete response to induction chemoimmunotherapy in locally advanced nasopharyngeal carcinoma.

OBJECTIVE: To develop and externally validate a pretreatment multiparametric MRI-based combined imaging model integrating conventional radiomics, habitat radiomics, and 2.5D deep learning features for predicting early complete response (CR) after induction chemoimmunotherapy in locally advanced nasopharyngeal carcinoma (LANPC) METHODS: This retrospective study included 500 patients with LANPC who ...

Integration of inflammatory and nutritional biomarkers with machine learning enhances prediction of progesterone response in fertility-preserving endometrial carcinoma management.

BACKGROUND: Endometrial carcinoma (EC) and atypical endometrial hyperplasia (AEH) increasingly affect young women, posing challenges for fertility preservation. The inflammatory and nutritional status have been shown to significantly influence disease outcomes, especially in cancer. However, no studies have systematically investigated the predictive value of inflammation and nutrition scores for c...

Precision therapeutics and innovative clinical trial design in neurodegenerative diseases.

Neurodegenerative diseases are biologically heterogeneous disorders characterized by progressive neuronal dysfunction, overlapping molecular pathologi...

Unraveling Bone-Skin Crosstalk Enables miRNA Nanoformulation for Cutaneous Neurovascular Reconstruction in Diabetic Mice.

The clinical intractability of diabetic foot ulcers stems from a profound uncoupling of cutaneous neurovascular networks, rendering standard metabolic...

Deep learning for preoperative MRI-based endometrial cancer staging prediction.

Endometrial carcinoma ranks among the most common malignancies of the female reproductive system. Accurate early-stage staging is essential for devisi...

AI in predicting the macrotrabecular-massive subtype of HCC and informing treatment selection: a multi-center and prospective validation study.

The macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) is associated with aggressive biology and poor prognosis. We aimed to deve...

Geometric-aware deep learning for deciphering tissue structure from spatially resolved transcriptomics.

Recent advances in spatially resolved transcriptomics have enabled large-scale measurement of gene expression while preserving spatial context, facili...

Integrative single-cell and spatial transcriptomic analysis reveals a lactate-driven crosstalk between NFATc4⁺ tumor cells and SPP1⁺ macrophages in glioblastoma.

BACKGROUND: Glioblastoma (GBM) remains a lethal brain tumor with limited therapeutic options. Metabolic reprogramming, particularly lactate metabolism...

Deep learning-based malignancy probability estimation of pulmonary nodules in PET/CT imaging.

OBJECTIVE: The current BTS guidelines recommend evaluation of suspicious pulmonary nodules using [18F]FDG-PET/CT imaging, followed by Herder model ris...

The role of serologic biomarkers "liquid biopsy" in the fight against breast cancer: From biological foundations to clinical impact.

Liquid biopsy, analyzing circulating tumor-derived components, including ctDNA, circulating tumor cells, microRNAs, and exosomes, has emerged as a key...

Mapping oral-systemic health relationships: a data-driven analysis of co-occurrence patterns in biomedical literature.

OBJECTIVE: To systematically map co-occurrence patterns between systemic medical conditions and oral diseases in the biomedical literature. MATERIALS ...

Periodic surveillance of intraductal papillary mucinous neoplasms: gaps in evidence and future directions.

Intraductal papillary mucinous neoplasm (IPMN) is a well-established precursor to pancreatic cancer; however, its generally indolent biological behavi...

Comparison of radiomics handcrafted features and deep features in 18F-FDG PET/CT for differentiating benign and malignant persistent pulmonary ground-glass nodules.

BACKGROUND: The differentiation between benign and malignant persistent pulmonary ground-glass nodules (GGNs) remains challenging, and the relative va...

Glycosylation Signatures of Thyroglobulin in Papillary Thyroid Carcinoma.

Thyroglobulin (Tg) is a clinically established biomarker for thyroid cancer; however, its diagnostic specificity remains limited due to confounding be...

Combining pathology artificial intelligence and genomic biomarkers to refine long-term postprostatectomy outcome prediction.

BACKGROUND: A multimodal AI (MMAI) model has been validated in prostate biopsy specimens to guide treatment intensification in men receiving radiation...

Machine learning prediction of local control after Gamma Knife radiosurgery to post-resection cavities from brain metastases: a proof-of-concept study.

BACKGROUND: Large symptomatic brain metastases require initial surgical resection. However, local control (LC) after Gamma Knife radiosurgery (GKRS) t...

A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing.

Cell-free DNA (cfDNA) in body fluids enables noninvasive cancer detection. Multifeature artificial intelligence (AI) can improve sensitivity by integr...

Pulmonary nodule prediction in the multi-omics era: integrating radiomics, AI, liquid biopsy, and airway classifiers.

Low-dose CT (LDCT) lung cancer screening significantly reduces mortality but has dramatically increased the detection of pulmonary nodules. Most of th...

A Multimodal Multitask Deep Learning Model Based on Ultrasound RF Signals for Joint Assessment of Breast Masses and Axillary Lymph Nodes Status.

PURPOSE: Developing a deep learning model to simultaneously evaluate lymph node status and distinguish between benign and malignant breast masses has ...

Identification of therapeutic targets and postoperative recurrence prediction model construction for hepatocellular carcinoma based on systematic mendelian randomization.

BACKGROUND AND STUDY AIMS: Hepatocellular carcinoma (HCC) has a high risk of postoperative recurrence. This study aimed to develop a transcriptome-bas...