Oncology/Hematology

Deep Learning Artificial Intelligence and Restriction Spectrum Imaging for Patient-level Detection of Clinically Significant Prostate Cancer on Biparametric Magnetic Resonance Imaging.

BACKGROUND AND OBJECTIVE: Our aim was to evaluate whether combining the maximum restriction score derived from restriction spectrum imaging (RSIrsmax) with deep learning (DL) models can enhance patient-level detection of clinically significant prostate cancer (csPCa) in comparison to Prostate Imaging-Reporting and Data System (PI-RADS) or RSIrsmax alone. METHODS: A total of 1892 patients from seve...

Application of radiomics in head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is the most prevalent histopathological subtype of head and neck malignancies. Owing to the lack of early specific symptoms, the majority of patients are diagnosed at intermediate or advanced stages, which is associated with an unfavorable prognosis and a substantial decline in quality of life. Radiomics, which leverages large-scale medical imaging dat...

From wrinkles to malignancy: small-molecule-mediated stem cell approaches in skin aging.

Skin aging is driven by the progressive exhaustion of stem cell niches, epigenetic drift, and accumulation of senescent cells, which together promote ...

Sequential glioblastoma segmentation via topological data analysis and spatial adjacency.

Segmenting glioblastoma in medical imaging remains challenging due to the tumor's irregular shape, heterogeneous texture, and poorly defined boundarie...

Multidisciplinary Team Diagnosis and Treatment of well-differentiated thyroid carcinoma: Current Landscape and Future Prospects.

BACKGROUND: The incidence of thyroid cancer has increased markedly in recent years, largely driven by well-differentiated thyroid carcinoma (WDTC). WD...

Protocol for non-invasive tumor monitoring and diagnosis based on interpretable deep learning.

Tumor-specific DNA methylation profiling in plasma cell-free DNA (cfDNA) offers a promising approach for non-invasive tumor detection. Here, we presen...

Screening for Tumor Microtube-Targeting Drugs Identifies PKC Modulators as Multipotent Inhibitors of Glioblastoma Progression.

UNLABELLED: Glioblastomas are incurable primary brain tumors that depend on neural-like cellular processes, tumor microtubes (TM), to invade the brain...

Synergistic DBNDD1-GDF15 Signaling Activates the NF-κB Pathway to Promote Colorectal Cancer Progression.

UNLABELLED: Colorectal cancer is a highly lethal gastrointestinal tract malignancy whose pathogenesis and molecular drivers are not fully understood. ...

Machine Learning Models for Posttransplant Lymphoproliferative Disorder (PTLD) Risk Prediction in Thoracic Transplantation.

Posttransplant lymphoproliferative disorder (PTLD) is the second most common malignancy in thoracic transplant recipients and is associated with poor ...

Implementation of artificial intelligence in palliative and supportive care for people with cancer: A scoping review.

BACKGROUND: Cancer remains a leading global health burden. Artificial intelligence offers new opportunities to address complex physical and psychologi...

Multi-omics profiling of chronic immune-mediated skin diseases: SKINERGY protocol and strategic evaluation.

BACKGROUND: The Dutch flagship project Next Generation ImmunoDermatology (NGID) aims to profile five chronic immune-mediated inflammatory skin disease...

Halide perovskite scintillators for X-ray detection: from structure to engineering.

Halide perovskites (HPs) and their derivatives are emerging as a prominent class of materials for ionizing radiation detection. A unique combination o...

Mamba-based Deep Learning Approach for Sleep Staging on a Wireless Multimodal Wearable System Without Electroencephalography.

STUDY OBJECTIVES: We investigate a Mamba-based deep learning approach for sleep staging on signals from ANNE One (Sibel Health, Chicago, IL), a non-in...

Machine Learning-Based Pathomics Signature in Predicting MSH2 Expression and Prognosis in Gastric Cancer.

BACKGROUND: Gastric cancer (GC) is one of the most prevalent and lethal gastrointestinal malignancies. MutS homolog 2 (MSH2), a DNA mismatch repair pr...

Interpretable deep learning model of circulating genomics for quantitative survival prediction in advanced non-small cell lung cancer.

PURPOSE: Accurate quantitative survival prediction in advanced non-small cell lung cancer (NSCLC) remains an unmet clinical need. While liquid biopsy ...

AI-FLEET: Phase I-Multimodal Deep Learning Model for Phyllodes Tumor Classification.

BACKGROUND: Fibroepithelial breast lesions, including fibroadenomas and phyllodes tumors (PTs), can be difficult to classify on needle biopsy. Misclas...

A High Magnifications Histopathology Image Dataset for Oral Squamous Cell Carcinoma Diagnosis and Prognosis.

Oral Squamous Cell Carcinoma (OSCC) is a prevalent and aggressive malignancy where deep learning-based computer-aided diagnosis and prognosis can enha...

Intraoperative biopsy imaging of lung cancer risk.

BACKGROUND: Before surgical resection of lung tumor, intraoperative biopsy is needed for cancer diagnosis, while current techniques that guide biopsy ...

STAR (stroma-tumor AI risk) assessment: association of AI-derived tumor-stroma proportion with patient survival provides added prognostic value beyond KELIM in epithelial ovarian cancer.

BACKGROUND: There remains a critical need for prognostic biomarkers of treatment response in epithelial ovarian cancer (EOC). The KELIM score, derived...

Label-free serum SERS combined with RFE-GBDT algorithm for non-invasive screening of liver cancer.

Early diagnosis of liver cancer is crucial for developing clinical treatment strategies and improving patient survival rates. However, current diagnos...