Subtle Medical

At a glance

Pricing

Enterprise.

HIPAA

Not disclosed

SOC 2

Not disclosed

EHRs

—

Founded

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Bottom line

AI image enhancement (lower dose / faster acquisition).

Free tier available.

Overview

Pricing

What it costs

Free tier only; no paid plans publicly disclosed.

Source: vendor pricing page. Verified May 23, 2026.

Peer-reviewed coverage

What the literature says

3 peer-reviewed studies indexed on PubMed evaluate Subtle Medical in clinical contexts. The most relevant are shown below, ranked by editorial relevance score combining title match, study design, recency, and journal tier.

Artificial Intelligence's Capacity to Detect Subtle Medical Misinformation: A Novel Reverse Prompting Approach.

Bendary M, Ramzy N, Khater A, et al.· J Med Syst· 2025

Medical misinformation is a major public health concern. The public increasingly uses artificial intelligence (AI) tools for medical consultations. Therefore, concerns arise about their ability to detect and even correct subtle medical information that users may be embedding in users prompts. This study assessed the ability of different ChatGPT models in detecting and correcting such subtle misinformation. Fifty clinical plausible prompts with subtle medical misinformation were introduced separately to ChatGPT models 4o, 4.1-mini, and GPT-5. Prompts spanned Internal Medicine, Cardiology,…

An Artificial Intelligence System for Staging the Spheno-Occipital Synchondrosis.

Milani OH, Mills L, Nikho A, et al.· Orthod Craniofac Res· 2025

The aim of this study was to develop, test and validate automated interpretable deep learning algorithms for the assessment and classification of the spheno-occipital synchondrosis (SOS) fusion stages from a cone beam computed tomography (CBCT). The sample consisted of 723 CBCT scans of orthodontic patients from private practices in the midwestern United States. The SOS fusion stages were classified by two orthodontists and an oral and maxillofacial radiologist. The advanced deep learning models employed consisted of ResNet, EfficientNet and ConvNeXt. Additionally, a new attention-based model…

Performance of a deep learning enhancement method applied to PET images acquired with a reduced acquisition time.

Ciborowski K, Gramek-Jedwabna A, Gołąb M, et al.· Nucl Med Rev Cent East Eur· 2023

This study aims to evaluate the performance of a deep learning enhancement method in PET images reconstructed with a shorter acquisition time, and different reconstruction algorithms. The impact of the enhancement on clinical decisions was also assessed. Thirty-seven subjects underwent clinical whole-body [18F]FDG PET/CT exams with an acquisition time of 1.5 min per bed position. PET images were reconstructed with the OSEM algorithm using 66% counts (imitating 1 min/bed acquisition time) and 100% counts (1.5 min/bed). Images reconstructed from 66% counts were subsequently enhanced using the S…

See all on PubMed