Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Modeling in Therapy01:26

Modeling in Therapy

Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in situations...
Theoretical Approaches to Psychological Disorder01:29

Theoretical Approaches to Psychological Disorder

The development of psychological disorders, which are characterized by deviant, maladaptive, and personally distressing behaviors, has been explored through several theoretical approaches.
Biological approach
The biological approach posits that internal, organic factors are the primary causes of such disorders. This perspective emphasizes brain structure and function, genetic predispositions, and neurotransmitter imbalances. For example, schizophrenia has been associated with both genetic...
Models of Health Promotion and Illness Prevention I01:25

Models of Health Promotion and Illness Prevention I

A model is a theoretical way to understand a concept or an idea. Models can overcome barriers to health regardless of diverse economic and cultural backgrounds. In addition, models make the task easier by providing different ways to approach complex issues. There are two major health promotion models: the health belief model and the health promotion model.
The health belief model (HBM) attempts to predict health-related behavior in specific belief patterns. According to the HBM, a person's...
Theory of Attribution II: Kelley's Covariation Theory01:29

Theory of Attribution II: Kelley's Covariation Theory

Attribution theory plays a crucial role in social psychology, helping to explain how individuals interpret the causes of behavior. One prominent model within this field is Harold Kelley's covariation theory, which provides a systematic approach to determining whether internal traits or external circumstances drive a person's actions. The model posits that individuals rely on three key types of information—consensus, consistency, and distinctiveness—to make these judgments.Consensus: Comparing...
Psychosis: Goals of Pharmacotherapy01:26

Psychosis: Goals of Pharmacotherapy

Antipsychotic drugs are a crucial treatment method for acute and chronic psychoses, bipolar illness, and behavioral disorders. The selection of these drugs depends on several factors, including the state of the disease, clinical judgment, possible drug interactions, and the patient's sensitivity to adverse effects. In immediate scenarios, such as delirium and dementia, short-term treatment with low doses of high-potency typical or atypical agents can effectively manage symptom exacerbation. For...
Theory of Attribution I: Correspondent Inference Theory01:15

Theory of Attribution I: Correspondent Inference Theory

Correspondent inference theory, proposed by Jones and Davis in 1965, seeks to explain how individuals infer stable personality traits from observed behaviors. It suggests that people attribute actions to underlying dispositions rather than external circumstances, particularly when the behavior appears intentional and socially significant.Voluntary Behavior and Dispositional AttributionAccording to this theory, individuals are more likely to attribute behavior to personal traits when it appears...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

eIF3e-mediated translational checkpoint maintains immune tolerance and prevents lymphoid malignancy.

The Journal of experimental medicine·2026
Same author

A Dual-Ion Source GC-HRMS Nontargeted Screening Strategy for Comprehensive Profiling of G-Series Nerve Agents and Related Chemicals.

Analytical chemistry·2026
Same author

Elucidation of Fragmentation Pathways and GC-HRMS Nontargeted Screening of V-Series Nerve Agent-Related Compounds: Alkylthiophosphonates.

Analytical chemistry·2026
Same author

Screening and SPR-guided maturation of anti-ricin cyclononapeptide for high-sensitivity fluorescent LFA integrated with ultracompact handheld reader.

Talanta·2026
Same author

Efficacy and safety of remimazolam tosylate for sedation in ICU patients: A multicenter, randomized, phase 2 study.

Journal of intensive medicine·2026
Same author

Validation of SOFA-2 score in sepsis and exploration of its extension with additional immune markers.

Journal of intensive medicine·2026

Related Experiment Video

Updated: Jul 15, 2026

Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia
13:08

Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia

Published on: December 2, 2015

PathFound: An agentic multimodal model activating evidence-seeking pathological diagnosis.

Shengyi Hua1, Jianfeng Wu2, Tianle Shen1

  • 1Qing Yuan Research Institute, Shanghai Jiao Tong University, Shanghai, 200240, Shanghai, China.

Medical Image Analysis
|July 13, 2026
PubMed
Summary

PathFound, an agentic multimodal model, enhances pathological diagnosis by seeking evidence, unlike static models. This proactive approach improves accuracy and discovers subtle details for better diagnostic outcomes.

Keywords:
Agentic large language modelComputational pathologyLarge multimodal modelMulti-turn interactionReinforcement learning

More Related Videos

Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Related Experiment Videos

Last Updated: Jul 15, 2026

Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia
13:08

Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia

Published on: December 2, 2015

Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Area of Science:

  • Computational pathology
  • Artificial intelligence in medicine
  • Multimodal machine learning

Background:

  • Current pathological foundation models use static inference, analyzing whole-slide images once.
  • This static approach lacks reassessment and targeted evidence acquisition for ambiguous diagnoses.
  • Clinical workflows involve iterative observation and further examination requests for hypothesis refinement.

Purpose of the Study:

  • To propose PathFound, an agentic multimodal model for evidence-seeking inference in pathological diagnosis.
  • To develop a model that mimics clinical diagnostic workflows for improved accuracy.
  • To enable proactive information acquisition and diagnosis refinement.

Main Methods:

  • PathFound integrates pathological visual foundation models, vision-language models, and reinforcement learning.
  • The model progresses through diagnosis, evidence-seeking, and decision stages.
  • Reinforcement learning trains the model for proactive information acquisition.

Main Results:

  • Adopting an evidence-seeking strategy consistently improves diagnostic accuracy across multimodal models.
  • PathFound achieves state-of-the-art diagnostic performance in diverse clinical scenarios.
  • The model demonstrates potential in discovering subtle pathological details like nuclear features and local invasions.

Conclusions:

  • Agentic, evidence-seeking workflows significantly enhance computational pathology.
  • PathFound represents a novel approach to pathological diagnosis, improving accuracy and detail discovery.
  • The model shows promise for real-world clinical applications in pathology.