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Technology#Social Media📝 BlogAnalyzed: Jan 3, 2026 06:06

FusenBoard: A Board-Type SNS Service for Posting Like Sticking Sticky Notes - A Story of Creation by Vibe Coding

Published:Dec 29, 2025 04:09
1 min read
Zenn ChatGPT

Analysis

The article introduces FusenBoard, a board-type SNS service designed for quick note-taking and revisiting information without the fatigue of a timeline-based SNS. It highlights the service's core functionality: creating boards, defining themes, and adding short-text sticky notes. The article promises an accessible explanation of the service's features, ideal use cases, and the development process, including the use of generative AI.
Reference

““I want to make a quick note,” “I want to look back later,” “But timeline-based SNS is tiring” — when you feel like that, FusenBoard is usable with the feeling of sticking sticky notes.”

PermalinkZenn ChatGPT
Research Paper#Survival Analysis, Deep Learning, Time-dependent Exposures🔬 ResearchAnalyzed: Jan 3, 2026 16:14

Deep Learning for Cumulative Effects in Survival Analysis

Published:Dec 29, 2025 00:22
1 min read
ArXiv

Analysis

This paper introduces CENNSurv, a novel deep learning approach to model cumulative effects of time-dependent exposures on survival outcomes. It addresses limitations of existing methods, such as the need for repeated data transformation in spline-based methods and the lack of interpretability in some neural network approaches. The paper highlights the ability of CENNSurv to capture complex temporal patterns and provides interpretable insights, making it a valuable tool for researchers studying cumulative effects.
Reference

“CENNSurv revealed a multi-year lagged association between chronic environmental exposure and a critical survival outcome, as well as a critical short-term behavioral shift prior to subscription lapse.”

PermalinkArXiv
Paper#Computer Vision, Event Cameras, Calibration🔬 ResearchAnalyzed: Jan 3, 2026 20:02

Line-Based Event Camera Calibration

Published:Dec 27, 2025 02:30
1 min read
ArXiv

Analysis

This paper introduces a novel method for calibrating event cameras, a type of camera that captures changes in light intensity rather than entire frames. The key innovation is using lines detected directly from event streams, eliminating the need for traditional calibration patterns and manual object placement. This approach offers potential advantages in speed and adaptability to dynamic environments. The paper's focus on geometric lines found in common man-made environments makes it practical for real-world applications. The release of source code further enhances the paper's impact by allowing for reproducibility and further development.
Reference

“Our method detects lines directly from event streams and leverages an event-line calibration model to generate the initial guess of camera parameters, which is suitable for both planar and non-planar lines.”

PermalinkArXiv
Research#LLM🔬 ResearchAnalyzed: Jan 10, 2026 13:19

Advancing Medical Reasoning in LLMs: Training & Evaluation

Published:Dec 3, 2025 14:39
1 min read
ArXiv

Analysis

This ArXiv paper likely explores how Large Language Models (LLMs) can be trained and evaluated to perform medical reasoning based on established guidelines. The research's focus on structured evaluations and adherence to medical guidelines is crucial for the safe and reliable deployment of LLMs in healthcare.
Reference

“The paper focuses on the training and evaluation of LLMs for guideline-based medical reasoning.”

PermalinkArXiv
Research#AI Agent🔬 ResearchAnalyzed: Jan 10, 2026 14:40

EchoAgent: AI-Powered Echocardiography Analysis Advances

Published:Nov 17, 2025 22:06
1 min read
ArXiv

Analysis

The EchoAgent paper, found on ArXiv, represents progress in applying AI to medical imaging. Its focus on guideline-centric reasoning suggests a step toward more reliable and clinically relevant AI solutions.
Reference

“The paper focuses on a Guideline-Centric Reasoning Agent for Echocardiography Measurement and Interpretation.”

PermalinkArXiv