·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Music streamer Deezer says more than 50% of daily uploads are AI-generated2h◆Halliday’s latest smart glasses feature a much-improved display2h◆America needs to stop getting shocked by Chinese AI4h◆Advancing next-gen AI with materials science innovation5h◆Gritt exits stealth with $32 million for robots to build solar plants — then, everything else5h◆Capacity and Redundancy Trade-offs in Multi-Task Learning11h◆Predictive Training with Latent Imagination for Visual Quadruped Navigation11h◆Where Not to Learn: Prior-Aligned Training with Subset-based Attribution Constraints for Reliable Decision-Making11h◆Did We Actually Fix It? An Independent Adversarial Stress-Test of Post-Point-Adjustment Evaluation Metrics for Time-Series Anomaly Detection11h◆Supervised Reward Inference11h◆PPO-HSC: An Exploratory Reinforcement Learning Framework Based on Wide-Area Policy Coverage Optimization11h◆Is Progressive Disclosure All You Need for Long-Context Agents?11h◆It Depends on the Dataset: When a Brain-Encoding Model's Predicted Responses Beat Their Visual Backbone for Video Memorability11h◆DMFNet: Dual-Backbone Multiscale Fusion Network for Urban Scene Classification11h◆Oracle Gap and Signal Fidelity: A Fixed-Pool Diagnostic for Test-Time Collaboration11h◆Scientific reasoning does not reliably translate into scientific forecasting in frontier AI11h◆Language Triggers Hijack Language Circuits: A Mechanistic Analysis of Backdoor Behaviors in Large Language Models11h◆AI-Augmented Human Resource Management? Insights from German companies11h◆When to Use Extra Context: Evidence-Grounded Terminology Adaptation for Simultaneous Speech Translation11h◆Octo-planner: On-device Language Model for Planner-Action Agents11h◆Music streamer Deezer says more than 50% of daily uploads are AI-generated2h◆Halliday’s latest smart glasses feature a much-improved display2h◆America needs to stop getting shocked by Chinese AI4h◆Advancing next-gen AI with materials science innovation5h◆Gritt exits stealth with $32 million for robots to build solar plants — then, everything else5h◆Capacity and Redundancy Trade-offs in Multi-Task Learning11h◆Predictive Training with Latent Imagination for Visual Quadruped Navigation11h◆Where Not to Learn: Prior-Aligned Training with Subset-based Attribution Constraints for Reliable Decision-Making11h◆Did We Actually Fix It? An Independent Adversarial Stress-Test of Post-Point-Adjustment Evaluation Metrics for Time-Series Anomaly Detection11h◆Supervised Reward Inference11h◆PPO-HSC: An Exploratory Reinforcement Learning Framework Based on Wide-Area Policy Coverage Optimization11h◆Is Progressive Disclosure All You Need for Long-Context Agents?11h◆It Depends on the Dataset: When a Brain-Encoding Model's Predicted Responses Beat Their Visual Backbone for Video Memorability11h◆DMFNet: Dual-Backbone Multiscale Fusion Network for Urban Scene Classification11h◆Oracle Gap and Signal Fidelity: A Fixed-Pool Diagnostic for Test-Time Collaboration11h◆Scientific reasoning does not reliably translate into scientific forecasting in frontier AI11h◆Language Triggers Hijack Language Circuits: A Mechanistic Analysis of Backdoor Behaviors in Large Language Models11h◆AI-Augmented Human Resource Management? Insights from German companies11h◆When to Use Extra Context: Evidence-Grounded Terminology Adaptation for Simultaneous Speech Translation11h◆Octo-planner: On-device Language Model for Planner-Action Agents11h◆
News/MLPTR-CC: Multi-label Pathology Test Recommendation using Classifier Chains and SHAP
arxiv
PublishedJuly 15, 2026 at 4:00 AM
—neutral

MLPTR-CC: Multi-label Pathology Test Recommendation using Classifier Chains and SHAP

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2607.08299v2 Announce Type: replace Abstract: Diagnostic decision making often relies on a sequence of pathology tests that bridge patient symptoms and final disease diagnosis. Existing clinical decision-support systems typically focus on predicting single diseases and do not explicitly recomm

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

// no spam · unsubscribe one-click · free forever

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivCapacity and Redundancy Trade-offs in Multi-Task Learning11harxivPredictive Training with Latent Imagination for Visual Quadruped Navigation11harxivWhere Not to Learn: Prior-Aligned Training with Subset-based Attribution Constraints for Reliable Decision-Making11harxivDid We Actually Fix It? An Independent Adversarial Stress-Test of Post-Point-Adjustment Evaluation Metrics for Time-Series Anomaly Detection11h
The Bubble Brief
WEEKLY

Read AI insights every Tuesday — top movers, new releases, story of the week.

// no spam · unsubscribe one-click · free forever

Originally published on arxiv ↗
HomeModelsNews