Results 61 to 70 of about 2,925,891 (315)

Subjective Expected Utility with State-Dependent but Action/Observation-Independent Preferences

open access: yesRisks, 2018
Under state-dependent preferences, probabilities and units of scale of state-dependent utilities are not separately identified. In standard models, only their products matter to decisions.
Jacques H. Drèze
doaj   +1 more source

Foundation Model‐Enabled Multimodal Deep Learning for Prognostic Prediction in Colorectal Cancer with Incomplete Modalities: A Multi‐Institutional Retrospective Study

open access: yesAdvanced Science, EarlyView.
FLARE, a multimodal AI framework, combines pathology slides, radiology scans, and clinical reports to predict colorectal cancer outcomes, even when some tests are missing. Evaluated retrospectively in 1679 patients from four medical centers, it consistently achieved the best prognostic accuracy and clearly separated high‐ and low‐risk groups.
Linhao Qu   +6 more
wiley   +1 more source

Context Effects in the Judgment of Visual Relative-Frequency: Trial-by-Trial Adaptation and Non-linear Sequential Effect

open access: yesFrontiers in Psychology, 2018
Humans' judgment of relative-frequency, similar to their use of probability in decision-making, is often distorted as an inverted-S-shape curve—small relative-frequency overestimated and large relative-frequency underestimated.
Xiangjuan Ren   +5 more
doaj   +1 more source

Red Blood Cells Internalize Extracellular DNA via Apoptotic Bodies with Clinical Relevance to Cancer Patients

open access: yesAdvanced Science, EarlyView.
Mature red blood cells (RBCs) can capture extracellular DNA, with short fragments homologous to cfDNA. This uptake is mediated by apoptotic bodies, which induce RBC oxidative stress, deformation, and accelerated in vivo clearance. The rbcDNA abundance correlates with tumor burden and therapeutic response, highlighting its potential as a liquid biopsy ...
Zihang Zeng   +20 more
wiley   +1 more source

Unpaired Learning‐Enabled Nanotube Identification from AFM Images

open access: yesAdvanced Science, EarlyView.
Identifying nanotubes on rough substrates is notoriously challenging for conventional image analysis. This work presents an unpaired deep learning approach that automatically extracts nanotube networks from atomic force microscopy images, even on complex polymeric surfaces used in roll‐to‐roll printing.
Soyoung Na   +10 more
wiley   +1 more source

Fears and realisations of employment insecurity [PDF]

open access: yes, 2009
We investigate the validity of subjective data expectations of job loss and on the probability of re-employment consequent on job loss, by examining associations between expectations and realisations.
Dickerson, A., Green, F.
core  

HiST: Histological Images Reconstruct Tumor Spatial Transcriptomics via MultiScale Fusion Deep Learning

open access: yesAdvanced Science, EarlyView.
HiST, a multiscale deep learning framework, reconstructs spatially resolved gene expression profiles directly from histological images. It accurately identifies tumor regions, captures intratumoral heterogeneity, and predicts patient prognosis and immunotherapy response.
Wei Li   +8 more
wiley   +1 more source

The Psychology of Uncertainty and Three-Valued Truth Tables

open access: yesFrontiers in Psychology, 2018
Psychological research on people's understanding of natural language connectives has traditionally used truth table tasks, in which participants evaluate the truth or falsity of a compound sentence given the truth or falsity of its components in the ...
Jean Baratgin   +4 more
doaj   +1 more source

Expert Knowledge Elicitation: Subjective but Scientific

open access: yesAmerican Statistician, 2019
Expert opinion and judgment enter into the practice of statistical inference and decision-making in numerous ways. Indeed, there is essentially no aspect of scientific investigation in which judgment is not required.
A. O’Hagan
semanticscholar   +1 more source

Pathomics Signature for Prognosis and CA19‐9 Interception in Pancreatic Ductal Adenocarcinoma: A Real‐Life, Multi‐Center Study

open access: yesAdvanced Science, EarlyView.
This study develops a deep learning‐based pathomics model to predict survival outcomes in pancreatic cancer patients. The CrossFormer architecture analyzes routine H&E‐stained tissue slides, identifying key prognostic features including stromal patterns, cellular characteristics, and immune infiltration.
Qiangda Chen   +22 more
wiley   +1 more source

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