Latest AI and machine learning research in pathology for healthcare professionals.
Three-dimensional (3D) alignment is a key step in volume electron microscopy (vEM), aimed at addressing misalignment during data acquisition, thereby recovering the correct biological structures. However, automated 3D alignment has long been challenged by the dilemma between eliminating nonlinear distortions and capturing natural morphological variations inherent to biological specimens. Here, we ...
Prefibrotic primary myelofibrosis (prePMF) and essential thrombocythemia (ET) are distinct myeloproliferative neoplasms (MPNs) with overlapping clinical features, often leading to diagnostic uncertainty. We developed an artificial intelligence (AI) framework with human interpretability to distinguish prePMF from ET using digitized hematoxylin and eosin-stained bone marrow biopsy (BMB) slides. Trai...
Patients with Hashimoto's thyroiditis (HT) frequently present with concurrent nodular lesions such as nodular goiter and thyroid cancer (especially pa...
CONTEXT: Pediatric differentiated thyroid carcinoma (DTC) often presents with advanced disease but generally has excellent long-term survival. However...
PURPOSE: Hypervascular pancreatic ductal adenocarcinoma (PDAC) and mass-forming pancreatitis (MFP) represent a classic diagnostic mimicry on contrast-...
Psoriasis and eczema are chronic inflammatory skin diseases with overlapping histopathological features, which often lead to diagnostic uncertainty ev...
Fat-containing soft-tissue tumors encompass a broad spectrum of entities, ranging from indolent lipomas to aggressive liposarcomas, many of which shar...
This study aimed to develop and evaluate a machine learning pipeline using multiphase contrast-enhanced CT images and clinical data to classify renal ...
Bone metastasis affects approximately 40% of patients with non-small cell lung cancer (NSCLC), significantly impacting patient survival and prognosis....
Federated learning (FL) enables collaborative medical image analysis across decentralized institutions while preserving data privacy. However, real-wo...
Diagnosing myeloproliferative neoplasms (MPNs) is challenging due to the nuanced and overlapping clinical manifestations of the various subtypes. Prec...
Early identification of malignant ovarian tumors is critical for informing treatment decisions and enhancing patients' quality of life. As the third m...
BACKGROUND: Lung cancer is the leading cause of cancer-related deaths. Diagnosis at late stages is common due to the largely non-specific nature of pr...
The suprachiasmatic nucleus (SCN) is considered the master pacemaker of the circadian clock in mammals, but our current knowledge of the SCN is mostly...
OBJECTIVES: To evaluate the performance of radiologists with artificial intelligence (AI)-based computer-aided detection (CAD) systems on automated br...
BACKGROUND: Accurate and noninvasive breast cancer grading and therapy monitoring remain critical challenges in oncology. Traditional methods often re...
AIMS: Annotation of liver biopsies for disease staging is increasingly aided by digital pathology; however, existing systems do not quantify inflammat...
PURPOSE: Intracranial calcifications are commonly found in adults and may represent either benign or pathological lesions. Conventional imaging modali...
Label-free detection of microRNAs (miRNAs) has emerged as a pivotal approach in molecular diagnostics, integrating the programmability of CRISPR syste...
Infertility has emerged as an increasingly serious global public health concern, affecting approximately one in six individuals of reproductive age wo...