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Built on peer-reviewed research

Built on peer-reviewed research

Peek is grounded in years of research in medical imaging, AI, and gastrointestinal diagnostics. Our work focuses on improving detection, analysis, and accessibility of screening technologies. Our team has contributed to peer-reviewed publications in leading conferences and journals, forming the scientific foundation behind Peek.

Peek is grounded in years of research in medical imaging, AI, and gastrointestinal diagnostics. Our work focuses on improving detection, analysis, and accessibility of screening technologies. Our team has contributed to peer-reviewed publications in leading conferences and journals, forming the scientific foundation behind Peek.

Reliable Restoration of Photon-Limited Wireless Capsule Endoscopy Images by Coupling Illumination Correction and Super Resolution

MICCAI

A reliability-conditioned diffusion framework for stable super-resolution under photon-limited capsule imaging.

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Reliable Restoration of Photon-Limited Wireless Capsule Endoscopy Images by Coupling Illumination Correction and Super Resolution

MICCAI

A reliability-conditioned diffusion framework for stable super-resolution under photon-limited capsule imaging.

Reliable Restoration of Photon-Limited Wireless Capsule Endoscopy Images by Coupling Illumination Correction and Super Resolution

MICCAI

A reliability-conditioned diffusion framework for stable super-resolution under photon-limited capsule imaging.

Read more

PeekNet: A Power and Efficiency-Enhanced Knowledge-Aware Network for Real-Time Capsule Endoscopy Image Classification

MICCAI 2025

A lightweight edge AI model enabling real-time on-device classification for energy-efficient capsule endoscopy.

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PeekNet: A Power and Efficiency-Enhanced Knowledge-Aware Network for Real-Time Capsule Endoscopy Image Classification

MICCAI 2025

A lightweight edge AI model enabling real-time on-device classification for energy-efficient capsule endoscopy.

PeekNet: A Power and Efficiency-Enhanced Knowledge-Aware Network for Real-Time Capsule Endoscopy Image Classification

MICCAI 2025

A lightweight edge AI model enabling real-time on-device classification for energy-efficient capsule endoscopy.

Read more

BEYOND AUROC: Evaluating Temporal Stability, False-Positive Load, and Uncertainty Calibration in Capsule Endoscopy Video AI

IEEE ISBI 2026 (VideoAI Workshop)

A video-aware evaluation framework revealing temporal instability, false-positive burden, and uncertainty gaps hidden by near-ceiling AUROC.

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BEYOND AUROC: Evaluating Temporal Stability, False-Positive Load, and Uncertainty Calibration in Capsule Endoscopy Video AI

IEEE ISBI 2026 (VideoAI Workshop)

A video-aware evaluation framework revealing temporal instability, false-positive burden, and uncertainty gaps hidden by near-ceiling AUROC.

BEYOND AUROC: Evaluating Temporal Stability, False-Positive Load, and Uncertainty Calibration in Capsule Endoscopy Video AI

IEEE ISBI 2026 (VideoAI Workshop)

A video-aware evaluation framework revealing temporal instability, false-positive burden, and uncertainty gaps hidden by near-ceiling AUROC.

Read more

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©

2026

Equitable Technologies Inc. All rights reserved.

Home

For Clinicians

Research

Navigation

Home
For Clinicians
Research
About us

Legal

Privacy Policy
Terms and Conditions

Our Offices

Boston (HQ)
Kuala Lumpur
Hyderabad
Email Address:
contact@screenwithpeek.com

Contact us

©

2026

Equitable Technologies Inc.
All rights reserved.