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Search results for “Pathology”

1,000+ results for "Pathology"

A new journal in pathology, forging frontiers in disease mechanism and translational innovation

The journal aims to pioneer a holistic understanding of disease as a dynamic ecosystem, integrating study of micro-environment, microbiota, metabolite, nervous system, and pathophysiology. Pathology Research covers a broad spectrum of pathology-related disciplines, including surgical and molecular pathology, artificial intelligence in ...

SourceHigher Education Press·TypeExperimental study·DateAug 31, 2026

PolyU research team develops trustworthy AI framework TRUECAM to enhance reliability of pathology AI in cancer diagnosis

The PolyU research team has developed TRUECAM, an integrated AI framework that ensures data and model trustworthiness in cancer diagnosis. The framework can assess the level of an AI's confidence in its diagnostic outputs and proactively prompts pathologists to review cases when uncertainty is high.

SourceThe Hong Kong Polytechnic University·JournalNature Biomedical Engineering·DateAug 20, 2026

Can AI become a trusted assistant for pathologists?

The article highlights the need for AI tools to provide interpretable and reportable results, with a focus on improving turnaround time, diagnostic consistency, and clinical decision-making. While AI is unlikely to replace pathologists, it can help convert tissue morphology into actionable evidence for better patient care

SourceScience China Press·JournalScience Bulletin·DateJul 31, 2026

AI tool helps predict bowel cancer relapse risk

A new AI tool developed by La Trobe University researchers can analyze routine pathology slides to predict stage-two bowel cancer patients at risk of relapse. The study analyzed over 1600 pathology slides and validated the findings across 1220 patients in three independent cohorts.

SourceLa Trobe University·JournalGastroenterology·TypeRandomized controlled/clinical trial·DateJul 28, 2026

Association for Molecular Pathology recognizes UW physician–scientist for exceptional service to the field

Daniel E. Sabath, a professor at UW Department of Laboratory Medicine and Pathology, has won the Association for Molecular Pathology's 2026 Meritorious Service Award for his dedication and effort over three decades. He is being honored for his leadership roles, scientific expertise, and collaborative spirit in advancing education and s...

Study finds little to no cortical lewy pathology in living Parkinson’s disease patients undergoing deep brain stimulation

Researchers found that patients with Parkinson's disease showing little to no Lewy bodies despite long-standing, clinically advanced disease. The study provides new insight into the relationship between clinical symptoms and neuropathological progression.

SourceThe Mount Sinai Hospital / Mount Sinai School of Medicine·Journalnpj Parkinson s Disease·TypeObservational study·DateJul 1, 2026

A lifecycle framework for digital pathology implementation: Integrating infrastructure, workflow, regulatory compliance, and ai readiness for sustainable adoption

A lifecycle framework helps laboratories overcome barriers to digital pathology adoption by integrating infrastructure, workflow redesign, validation, interoperability, and AI readiness. The framework addresses institutional governance, cybersecurity, education, and performance monitoring to ensure durable success.

SourceXia & He Publishing Inc.·JournalJournal of Clinical and Translational Pathology·DateJun 27, 2026

Artificial intelligence in breast pathology: Recent advances in multimodal models, explainability, and clinical applications

The review discusses key AI concepts, including algorithms, models, architectures, machine learning, deep learning, and multimodal models. It highlights their clinical applications, such as detection of lymph node metastases, Nottingham grading, biomarker quantification, risk stratification, and prognostic prediction.

SourceXia & He Publishing Inc.·JournalJournal of Clinical and Translational Pathology·DateJun 26, 2026

New framework renders AI trustworthy for cancer subtyping

Researchers have developed a versatile uncertainty-aware AI framework called TRUECAM that provides customizable accuracy guarantees for cancer subtype classifications. TRUECAM outperforms existing approaches to digital pathology AI uncertainty quantification, detecting out-of-scope inputs and improving fairness across sex and race.

SourceVanderbilt University Medical Center·JournalNature Biomedical Engineering·TypeData/statistical analysis·DateJun 23, 2026

Adoption paradox of artificial intelligence in computational pathology: a three-stage maturity model from algorithms to clinical integration

The study proposes a three-stage maturity model for AI integration in pathology, highlighting key barriers to clinical translation: data fragility, workflow misalignment, and institutional trust deficits. Infrastructure-first AI, workflow-embedded intelligence, and adaptive governance are proposed pathways toward sustainable clinical i...

SourceShanghai Jiao Tong University Journal Center·JournalLabMed Discovery·TypeNews article·DateJun 16, 2026

Researchers identify a key biological tipping point in Alzheimer’s disease

A study published in Nature Medicine reveals that distinct cellular programs and immune-cell states are associated with Alzheimer's disease progression and resilience. Microglial responses were found to be critical in determining whether Alzheimer's pathology leads to dementia, suggesting new avenues for therapies to prevent neurodegen...

SourceVlaams Instituut voor Biotechnologie·JournalNature Medicine·TypeExperimental study·DateJun 4, 2026

Recent advances in the diagnosis and treatment of fat accumulation in liver and pancreas

Researchers highlight latest developments in pathology, diagnosis, and treatment of MASLD and IPFD, revealing correlations with chronic diseases like liver cancer and pancreatic cancer. Innovative treatments, such as AI-driven approaches and organ-targeted therapies, show promise for precision prevention and therapy.

SourceChinese Medical Journals Publishing House Co., Ltd.·JournalPortal Hypertension & Cirrhosis·TypeSystematic review·DateJun 1, 2026

HKUST develops novel ai pathology system for accurate multi-cancer diagnosis without additional model training

The research team developed a novel AI pathology analysis system named PRET that can accurately recognize multiple types of cancer using only a minimal number of samples. PRET outperformed existing methods in 20 tasks, achieving high diagnostic accuracy rates and stable generalizability across different populations and regions.

SourceHong Kong University of Science and Technology·JournalNature Cancer·TypeData/statistical analysis·DateApr 21, 2026

Blake Warner named recipient of the 2026 AADOCR National Student Research Group Mentor Award

Blake Warner, a renowned expert in salivary disorders, has been awarded the 2026 AADOCR National Student Research Group Mentor Award. He leads an integrated clinic and research laboratory focused on deep characterization of disorders affecting the salivary glands. The award recognizes his outstanding mentorship in dental research.

A smarter way to build vaccines: UTMB scientists harness AI to target emerging alphaviruses

Researchers have developed an integrated reiterative pipeline that uses machine learning and structural biology to identify promising vaccine targets across multiple related viruses simultaneously. The system evaluates viral proteins to identify short fragments called epitopes that can trigger a strong immune response.

Alexander Kerr named recipient of the 2026 IADR Distinguished Scientist Award in Oral Medicine & Pathology Research

Alexander Kerr, NYU Clinical Professor, recognized for outstanding research on oral cavity squamous cell carcinoma and oral potentially malignant disorders. The IADR Distinguished Scientist Award is one of the highest honors bestowed by IADR, recognizing contributions to understanding oral health and disease mechanisms.

From pathology image to biological discovery: A journey with LazySlide

LazySlide enables systematic whole-slide image analysis using AI models and links visual patterns to text concepts. The study demonstrates its potential in analyzing tissue samples, identifying biological pathways, and reducing the barrier for applying advanced image analysis methods.

BU researchers identify specific protein and sugar molecules affected by aging, disease

Researchers at Boston University School of Medicine have discovered protein and sugar level changes that occur with aging and Alzheimer's disease brains. The study uses a unique mass spectrometry technique to capture detailed molecular information, providing new avenues for biomarker discovery and potential treatments.

SourceBoston University School of Medicine·JournalAnalytical and Bioanalytical Chemistry·TypeExperimental study·DateMar 3, 2026