Pathology

Artificial intelligence-driven label-free detection of chronic myeloid leukemia cells using ghost cytometry.

Early diagnosis and treatment initiation of chronic myeloid leukemia (CML) are considered to increase the rate of deep molecular response. However, the early diagnosis of CML is challenging due to the absence of clinical symptoms and peripheral blood test anomaly, especially at the timing of peripheral white blood cell count is within a normal range. This study explored the possibility of artifici...

Deep learning for smartphone-aided detection system of Helicobacter Pylori in gastric biopsy.

Helicobacter pylori (HP) have chronically infected more than half of the world's population and is a cause of chronic gastritis, peptic ulcers and gastric carcinoma. The manual detection of HP in a glass slide with a microscope is extremely time-consuming and might miss at least 14% of HP-positive cases due to eye fatigue of pathologists. Here, a total of 270 gastric biopsy specimens were selected...

An enhanced deep learning model for accurate classification of ovarian cancer from histopathological images.

Ovarian Cancer is a malignancy that develops from ovarian cells and is frequently characterized by aberrant cell proliferation that leads to the creat...

Fabrication of serum-based SERS-tailored 3D structures for thyroid cancer diagnosis.

Early detection of thyroid cancer improves patient survival rate from 51.9% to 99.9%. Fine needle aspiration cytology is the primary method for diagno...

Enhancing chronic wound assessment through agreement analysis and tissue segmentation.

Accurate monitoring of chronic wound progression is crucial for assessing healing dynamics. However, the current manual process of tissue segmentation...

Development and multicenter validation of on-site breast cancer diagnosis using paper spray ionization miniature mass spectrometry.

BACKGROUND: Conventional histopathological examination for breast core needle biopsy diagnosis is time-consuming and labor-intensive, leading to delay...

Shared gene signatures and molecular mechanisms link ankylosing spondylitis and rheumatoid arthritis.

Ankylosing spondylitis (AS) and rheumatoid arthritis (RA) are closely related autoimmune diseases with shared mechanisms that remain unclear. This stu...

Auto-Segmentation via deep-learning approaches for the assessment of flap volume after reconstructive surgery or radiotherapy in head and neck cancer.

Reconstructive flap surgery aims to restore the substance and function losses associated with tumor resection. Automatic flap segmentation could allow...

Identification of CXCR4 as a potential preventive gene in clear cell renal cell carcinoma from machine learning and immune analysis.

Clear cell renal cell carcinoma (ccRCC) represents a prevalent malignant kidney tumor characterized by high metastatic potential and recurrence rates....

Decoding the diagnostic biomarkers of mitochondrial dysfunction related gene variants in pediatric T cell acute lymphoblastic leukemia.

Mitochondrial dysfunction is crucial in the pathogenesis and drug resistance of pediatric T-cell acute lymphoblastic leukemia (T-ALL), a malignant hem...

Deep learning of structural morphology imaged by scanning X-ray diffraction microscopy.

Scanning X-ray nanodiffraction microscopy is a powerful technique for spatially resolving nanoscale structural morphologies by diffraction contrast. O...

Machine learning to detect melanoma exploiting nuclei morphology and Spatial organization.

Cutaneous melanoma is one of the most lethal forms of skin cancer, and its incidence is increasing globally. Its diagnosis typically relies on manual ...

Machine learning unveils hypoxia-immune gene hub for clinical stratification of thyroid-associated ophthalmopathy.

Thyroid-associated ophthalmopathy (TAO) is an autoimmune disorder affecting the orbit, potentially resulting in blindness. This study focused on the r...

A hybrid compound scaling hypergraph neural network for robust cervical cancer subtype classification using whole slide cytology images.

Cervical cancer is a major cause of mortality among women, particularly in low-income countries with insufficient screening programs. Manual cytologic...

Leveraging an ensemble of EfficientNetV1 and EfficientNetV2 models for classification and interpretation of breast cancer histopathology images.

Breast cancer is the second leading cause of cancer-related deaths among women, following lung cancer, as of 2024. Conventional cancer diagnosis relie...

Formulation of low temperature mixed mode crack propagation behavior of crumb rubber modified HMA using artificial intelligence.

Determining mixed mode fracture parameters asphalt concrete mixtures remains an engineering challenge due to non-homogeneity and inelasticity of the m...

Quantitative ultrasound classification of healthy and chemically degraded ex-vivo cartilage.

In this study, we explore the potential of ten quantitative (radiofrequency-based) ultrasound parameters to assess the progressive loss of collagen an...

Validation of an AI-enabled exome/transcriptome liquid biopsy platform for early detection, MRD, disease monitoring, and therapy selection for solid tumors.

Effective clinical management of patients with cancer requires highly accurate diagnosis, precise therapy selection, and highly sensitive monitoring o...

Deep learning-based lung cancer classification of CT images.

Lung cancer remains a leading cause of cancer-related deaths worldwide, with accurate classification of lung nodules being critical for early diagnosi...

The value of machine learning based on spectral CT quantitative parameters in the distinguishing benign from malignant thyroid micro-nodules.

BACKGROUND AND AIMS: More cases of thyroid micro-nodules have been diagnosed annually in recent years because of advancements in diagnostic technologi...