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Content by Michael Schubert:

Inside the Lab Technology and innovation

Inspiring Inventions

| Michael Schubert

The inventors of new diagnostic technologies discuss their innovations and how they can move laboratory medicine forward

Outside the Lab Profession

The Veterinary Pathologist

| Michael Schubert

Nicola Parry describes her career in veterinary pathology, including her views on the future and her experiences in giraffe autopsy!

Diagnostics Biochemistry and molecular biology

Molecular Diagnostics on the Rise

| Michael Schubert

Accurate, safe, and dependable diagnostic tools are crucial – and this is where molecular diagnostics has the opportunity to shine

Outside the Lab Profession

Wise Words

| Michael Schubert

We reflect on the wisdom we’ve gained from the leading pathologists and laboratory medicine professionals we’ve spoken to over the year

Inside the Lab Pathologists’ assistants

The Art of Grossing

| Michael Schubert, Cory Nash, Jesse McCoy

Pathologists’ assistants Cory Nash and Jesse McCoy unpick the AAPA’s Grossing Guidelines and provide an insight into the gross examination of tissue

Subspecialties Oncology

Beating the Biopsy

| Michael Schubert

A new approach to prostate cancer testing aims to decrease unnecessary biopsies and reduce over-treatment

Inside the Lab Laboratory management

The Value of One

| Michael Schubert

It’s easy to underestimate the importance of a single laboratory task or a single person – but to do so is a mistake

Inside the Lab Digital and computational pathology

Erasing Pathology’s Borders

| Michael Schubert

In today’s increasingly connected society, how can digital pathology facilitate long-distance diagnosis and ease resource pressures across the globe?

Inside the Lab Digital and computational pathology

A Renal Revolution

| Michael Schubert

Two new computational pathology tools offer promise in the challenging arena of renal pathology

Diagnostics Genetics and epigenetics

Unraveling Complexity

| Michael Schubert

A new kind of deep learning model uses nonlinear information to draw new associations between genes and diseases

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