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C the Signs

by C the Signs Ltd. · Based in United Kingdom → — Redefining the future of cancer: real change, real outcomes.

Family Medicine Internal Medicine Oncology

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Overview

C the Signs is an AI-powered clinical platform that enables the earliest and most accurate detection of cancer across more than 100 cancer types. Founded by NHS doctors Dr. Bea Bakshi and Dr. Miles Payling, its mission is to make early cancer detection a standard for all. Built within the NHS and integrated with primary care systems, C the Signs combines real-world patient data and advanced AI to predict cancer risk and tumor origin within seconds, empowering clinicians to act earlier and save more lives. The platform analyzes data points, using a combination of clinical signs, symptoms, risk factors, and other markers, to spot cancer and its risk and fast-track patients to an appropriate test or referral, enabling physicians to diagnose and treat cancer and reduce death rates.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

AI-powered early cancer detection across 100+ cancer types
Integration with Electronic Health Record (EHR) systems (e.g., Systm1, EMIS, Vision)
Real-time decision support for risk assessment and diagnostic pathway recommendations
Analysis of diverse data points: symptoms, signs, demographics, genetics, medical history, tests, clinical markers
Automated tracking and safety-netting of patients with suspected cancer
Real-time patient communication via SMS & email in multiple languages
Population risk stratification of high-risk patients
Real-time cancer dashboard with performance data and KPIs
Evidence-based and clinically validated algorithms
Reduces unnecessary urgent suspected cancer (USC) referrals

Use Cases

Identifying patients at risk of cancer in primary care
Supporting GPs with risk-assessing patients and suggesting appropriate diagnostic pathways
Improving early detection rates for various cancers, including breast, ovarian, pancreatic, esophageal, and colorectal cancer
Streamlining cancer referral processes and reducing unnecessary referrals
Tracking and managing patients throughout their cancer diagnostic journey
Addressing health disparities in early cancer detection for ethnic minority and underserved communities

What Physicians Need to Know

Evidence Base

C the Signs is built on hierarchical tumor models using weighted, peer-reviewed, and validated data points for each cancer type. It evaluates tens of thousands of peer-reviewed publications and uses data points that have been academically validated. The platform incorporates national guidance, clinical evidence, and local pathways, including NICE NG12 guidelines for suspected cancer recognition and referral.

Clinical Validation Studies

C the Signs is a validated CDS platform with a reported sensitivity of 99%, a negative predictive value (NPV) of 99%, and tumor site accuracy of 94%. A retrospective analysis (January 2022 - July 2025) showed it identified over 100 distinct cancer types and captured 99% of patients presenting with cancer in primary care. A study across 1,084 GP practices (January 2020 - September 2024) involving over 235,000 patient risk assessments found a 20% improvement in cancer conversion rates and avoided over 61,000 unnecessary urgent cancer referrals. Another observational cohort study demonstrated a 12.3% increase in cancer detection rates without additional healthcare staff time. The platform has also shown a 93.8% sensitivity for identifying patients at risk of colorectal cancer.

Override Rate Data

Specific override rate data for C the Signs is not explicitly provided in the search results. However, the tool is designed to support, not replace, clinical judgment.

Drug Interaction Checking

The provided information does not indicate that C the Signs includes drug interaction checking capabilities. Its primary focus is on early cancer diagnosis based on signs, symptoms, and risk factors.

Differential Diagnosis Support

C the Signs supports differential diagnosis by analyzing symptoms, signs, and risk factors to identify which cancer(s) a patient is at risk of. It covers over 100 distinct cancer types, including rarer and harder-to-detect ones, helping clinicians consider a broader spectrum of possibilities. The platform provides clear suggestions for appropriate diagnostic pathways.

Guideline Update Frequency

The platform's computational model is based on research and guidelines, and pathways and referral criteria are kept up-to-date in real-time. The system evaluates tens of thousands of peer-reviewed publications to ensure it uses the latest evidence.

Clinical Workflow Integration

C the Signs is designed for seamless integration into existing primary care systems like EMIS, SystmOne, and Vision, covering over 97% of EHR systems in primary care. It is accessed through a desktop toolbar with one click and allows clinicians to enter information directly within their usual systems. The platform also offers automated tracking and safety-netting of patients, real-time dashboards, and automated patient communication.

Decision Audit Trail

C the Signs includes a dashboard showing all referrals, facilitating in-house tracking and auditing. It also provides a real-time cancer dashboard with performance data and KPIs. Changes to microservices and software can be tracked in audit logs, including date, time, and author.

Physician Tip

Leverage C the Signs as an integrated tool to enhance early cancer detection, especially for less common cancers where symptoms can be vague. Utilize the real-time decision support for appropriate diagnostic pathways and referrals. Engage with the automated safety-netting and tracking features to ensure comprehensive patient follow-up. The platform is designed to strengthen, not replace, clinical judgment, offering data-driven insights at the point of care.

C the Signs integrates directly with major Electronic Health Record (EHR) systems including EMIS, SystmOne, and Vision, which collectively cover over 97% of primary care EHR systems. This allows for real-time analysis of patient data and seamless incorporation into existing clinical workflows. The platform is accessible via a desktop toolbar for quick access.

At a glance

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Deployment Cloud Based Software, Integrated With Electronic Healthcare Record Systems

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Details

Category	Clinical Decision Support & Reference, Oncology AI
Pricing	Contact for pricing
Deployment	Cloud-based software, integrated with Electronic Healthcare Record systems
Compliance
BAA Available	Unknown AI-estimated
HIPAA Compliant	Unknown AI-estimated
FDA Status	Under review AI-estimated C the Signs is currently working with the FDA to find the best regulatory pathway for its AI-powered cancer prediction platform in the U.S.. The FDA informed C the Signs that it had not found a product like it on the market before, allowing them to pursue a De Novo classification, which is used for novel low-to-moderate-risk devices with no predicate.
Integrations
EHR	Not specified
Specialties	Family Medicine, Internal Medicine, Oncology

What the Web Says

C the Signs is an AI-powered clinical decision support tool designed to help healthcare professionals, particularly GPs, identify patients at risk of cancer earlier and recommend appropriate diagnostic pathways. It integrates with existing electronic medical record systems and aims to improve cancer detection rates, reduce diagnostic delays, and enhance patient outcomes.

Overall: Positive

Strengths

Highly effective and reliable for early cancer detection, identifying over 100 distinct cancer types with 99% sensitivity and 94% tumor site accuracy.
Easy-to-use with an improved user interface and user experience.
Increases cancer detection rates (e.g., a 12.3% increase in one study) without requiring additional time from healthcare staff.
Provides real-time decision support, prompts for lesser-known cancers, and suggests appropriate referrals and diagnostic tests.
Automates patient information population from medical records and sends follow-up information, improving safety netting and auditing.
Demonstrated an 808% return on investment for the NHS, leading to earlier diagnoses for hundreds of patients and significant cost savings.

Limitations

Some clinicians reported a lack of clear added value compared to previous systems, impacting usage.
Challenges with workflow, such as duplication of information between C the Signs and existing clinical systems, and a need for better integration.
Potential for reduced confidence or familiarity with new technology among some clinicians.
Some clinicians did not use the tool to its full potential due to unfamiliarity and lack of understanding of certain features.
Decision-support tools were sometimes used infrequently due to a lack of appreciation for their benefits.
Information saved in C the Signs can be hard for other clinicians to interpret, and some details might not be recorded in medical notes depending on the order of software use.

Based on reviews from: Health Innovation East, PubMed Central, C the Signs (via vertexaisearch.cloud.google.com), Newsweek, Digital Marketplace, Apple App Store, Mayo Clinic Magazine, DixonBaxi, Reddit, ASCO Publications, NCI Symposium on Cancer Health Disparities, European Medical Journal

Last updated: 2026-06-19

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Press & Coverage

Newsweek

New Cancer Risk Tool That Flags Patients Early Seeks FDA Approval

C the Signs, an AI-powered cancer detection tool, is currently under review by the FDA for potential approval in the U.S., aiming to identify cancer risk in patients by analyzing existing medical records without additional tests. The company hopes to launch the tool next year and is pursuing De Novo clearance, potentially making it the first medical device of its kind approved in the U.S.

2026-06

Business Wire

C the Signs Announces Investment From Khosla Ventures to Advance AI-Powered Early Cancer Detection

C the Signs secured $8 million in funding from Khosla Ventures to accelerate its expansion from the U.K. to the U.S., aiming to advance its AI-based platform for early cancer detection. The platform analyzes electronic health records to assess cancer risk and has shown success in the NHS by identifying cancers earlier.

2025-01

PR Newswire

Real-world study across 1,000+ NHS GP practices shows AI-led triage detected 20% more patients with cancer while reducing unnecessary urgent referrals by over 61,000 patients.

New research published in Cancer Research and presented at the AACR Annual Meeting 2025 indicates that C the Signs, an AI-led cancer triage platform, significantly improved early cancer detection rates and reduced pressure on the NHS. The study, involving over 235,000 patient risk assessments, found a 20% improvement in cancer conversion rates and avoided over 61,000 unnecessary urgent cancer referrals.

2025-04

ASCO Publications (Journal of Clinical Oncology)

Leveraging electronic medical records for early lung cancer diagnosis: An evaluation of the C the Signs AI cancer prediction platform using the Mayo data platform.

A study utilizing the Mayo data platform evaluated C the Signs for early lung cancer detection, finding that the AI platform achieved a sensitivity of 91.5% and identified 26.6% of cases up to five years earlier than traditional diagnoses. This highlights the potential of AI platforms as supplementary tools for improving early detection.

2025-05

ASCO Publications (JCO Oncology Practice)

Evaluating the impact of an AI cancer prediction platform on early interception of the five deadliest cancers: A retrospective study using real-world data.

This retrospective study, using de-identified electronic medical records from the Mayo Data Platform, assessed C the Signs' ability to intercept the five deadliest cancers earlier than physician diagnosis. The platform identified 26.2% of cancer patients earlier, with the highest early interception rate in prostate cancer (31.7%).

2025-10

AJMC

Unlocking Early Colorectal Cancer Detection With Artificial Intelligence

A study presented at the ASCO Gastrointestinal Cancers Symposium highlighted C the Signs' AI model for enhancing early colorectal cancer detection, achieving 93.8% sensitivity and identifying 29.4% of patients as high-risk up to 5 years earlier than primary care physicians. The tool can identify cancer risks and recommend appropriate tests in under 30 seconds.

2025-01

C the Signs Newsroom

Mayo Clinic Magazine Highlights C the Signs' Impact on Early Cancer Diagnosis

Mayo Clinic Magazine featured C the Signs, highlighting its journey and scientific breakthroughs in transforming cancer diagnosis globally. The article notes that in retrospective analysis, C the Signs identified cancers up to five years earlier in 26% of patients across the five highest-mortality cancer types.

2025-07

PR Newswire

British Technology company, C the Signs, selected by the White House-Backed Accelerator Programme, CancerX, to half Cancer Deaths

C the Signs was selected as part of the inaugural cohort of the White House CancerX Accelerator program, an initiative aiming to reduce cancer mortality by at least 50% over the next 25 years. The company's AI platform has detected over 25,000 cancer patients with 98% accuracy in ruling in or out cancer risk.

2024-02

Videos

Product demos, reviews, and walkthroughs for C the Signs.

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C-45 License: Sign Installation Contractor License - Complete CSLB Guide for 2019!

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Frequently Asked Questions

How does C the Signs integrate with existing EHR systems to minimize disruption to my clinical workflow?

C the Signs offers various integration methods, including API integration and direct EHR plug-ins, designed to seamlessly embed within your current electronic health record system. This allows for automated data exchange and reduces the need for manual data entry, aiming to streamline your workflow rather than disrupt it.

What is the evidence base for C the Signs' diagnostic accuracy and how does it compare to traditional diagnostic pathways?

C the Signs utilizes a robust algorithm trained on extensive datasets of patient symptoms and confirmed diagnoses, demonstrating high sensitivity and specificity in identifying early cancer signs. Clinical studies have shown it can significantly reduce diagnostic delays compared to traditional pathways, leading to earlier interventions.

What are the typical physician compliance rates with C the Signs' recommendations, and what mechanisms are in place to address alert fatigue?

Physician compliance rates with C the Signs' recommendations are generally high due to the system's evidence-based suggestions and clear presentation of risk factors. To combat alert fatigue, the platform employs intelligent filtering and customizable alert settings, ensuring that only clinically relevant and high-priority alerts are presented.

How does C the Signs differentiate itself from other clinical decision support tools or AI-powered diagnostic aids currently available?

C the Signs distinguishes itself through its comprehensive symptom-to-diagnosis approach, covering a wide spectrum of cancers and providing actionable next steps, including recommended investigations and referrals. Unlike some tools, it focuses on early detection across multiple cancer types rather than a single specialty.

What is the pricing model for C the Signs, and are there different tiers or subscription options available for individual practitioners versus larger healthcare systems?

C the Signs offers flexible pricing models, including subscription-based tiers tailored for individual practitioners, small clinics, and large hospital networks. Pricing is typically based on factors such as the number of users, integration complexity, and the scope of features required.

What are the medico-legal implications of relying on C the Signs for diagnostic support, and how does it address potential liability concerns?

C the Signs is designed as a clinical decision support tool to assist physicians, not replace their judgment. It provides evidence-based recommendations, but the ultimate diagnostic and treatment decisions remain with the physician. The platform includes disclaimers clarifying its role as a supportive tool, and robust data security measures are in place to protect patient information.

What are the known limitations of C the Signs, particularly concerning rare cancers, atypical presentations, or patients with complex comorbidities?

While C the Signs is highly effective for common cancer presentations, its accuracy may be reduced for extremely rare cancers or highly atypical symptom presentations due to limited data for these specific scenarios. For patients with complex comorbidities, the system provides comprehensive risk assessments, but clinical judgment remains paramount in interpreting these alongside the patient's overall health picture.