The MyTwin blog

Understanding
preventive and predictive health

In-depth, sourced articles with no overblown promises — for patients, clinicians and employers.

Patient digital twins: definition, uses and limits

A patient digital twin is a personalized virtual model, fed with data about one person and designed to inform a decision or simulate how their health may evolve. That definition covers very different uses, from anatomical models to predictive systems. Here is how to tell them apart without overestimating what they can do.

September 14, 2026Read the article

Patients5 min read

Second medical opinion: when and how to get one

Asking for a second opinion is not challenging your doctor. It means seeking additional insight when a decision is serious, uncertain or hard to understand. To be useful, it takes a precise question, a complete medical file and a final conversation with the professionals involved in your care.

September 16, 2026Read the article

Patients5 min read

Personal health record: taking back control of your medical records

A useful personal health record is more than a pile of PDFs. It should help you find the right information, check where it comes from and share it with the right professional. Here is a practical method for organizing your medical history while protecting your privacy and respecting your doctor’s role.

September 16, 2026Read the article

Clinicians5 min read

Remote patient monitoring: building a care pathway that works

Remote monitoring does not improve a care pathway simply by collecting data. Its value depends on a precise indication, interpretable alerts, a team able to respond and continuous evaluation. This framework helps care teams move from yet another dashboard to a genuine care protocol.

September 16, 2026Read the article

Clinicians6 min read

AI in medical imaging: five conditions for trust

Strong performance on a dataset is not enough to make AI in medical imaging useful. Teams need to check its population, its role, its integration, its oversight and how it is monitored after deployment. Here are five conditions for moving from a technical demo to controlled clinical use.

September 16, 2026Read the article

Employers5 min read

Workplace heart health: how employers can help without playing doctor

Workplace heart health is not about collecting employees’ medical data. It combines supportive working conditions, information, voluntary participation and referral to the right professionals. This guide sets out a measurable approach that protects confidentiality while connecting collective prevention with individual care.

September 16, 2026Read the article

Patients5 min read

Predictive health: anticipating without claiming to predict the future

Predictive health does not read the future. It uses data to estimate the probability of an event or a change within a defined context. Well understood, it can support prevention. Poorly presented, it can create false certainties. Here are the key points for interpreting a risk score.

September 14, 2026Read the article

Clinicians4 min read

Real-world data: better patient monitoring between visits

Real-world data describes health and care outside of controlled research settings. It can enrich follow-up between two consultations, provided it is relevant, reliable and built into an action protocol. Its value comes not from the volume collected, but from the decisions it helps inform.

September 14, 2026Read the article

Employers4 min read

How to measure a workplace health prevention program

A prevention program should be judged neither by the number of apps purchased nor by a vague promise of savings. You need to measure its deployment, use, accessibility and effects, while protecting individual medical data. Here is a practical measurement framework for employers.

September 14, 2026Read the article

Employers4 min read

Personalizing workplace health prevention without monitoring employees

Employees don’t all have the same needs, but their employer must not know their medical situation. A prevention platform can resolve this tension by strictly separating the individual journey from collective program management. Here are the design principles that protect both trust and usefulness.

September 14, 2026Read the article

Understandingpreventive and predictive health

Patient digital twins: definition, uses and limits

Second medical opinion: when and how to get one

Personal health record: taking back control of your medical records

Remote patient monitoring: building a care pathway that works

AI in medical imaging: five conditions for trust

Workplace heart health: how employers can help without playing doctor

Predictive health: anticipating without claiming to predict the future

Real-world data: better patient monitoring between visits

How to measure a workplace health prevention program

Personalizing workplace health prevention without monitoring employees

Understanding
preventive and predictive health