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Digital and computational pathology

Outside the Lab Profession

The Digital Pioneer

| Liv Gaskill

We sit down with Rajendra Singh to talk all-things digital pathology, PathPresenter, and time management for pursuing your passion

Inside the Lab Digital and computational pathology

Aurora mScope: High-Value Higher Education

| Sponsored by Aurora mScope Inc.

Erik Yeo answers additional questions regarding Aurora mScope Education's real-world utility

Inside the Lab Digital and computational pathology

Success Through Centralization?

| Geoffrey Metcalf, Meredith James, Roberto Gianani

The path to realizing digital pathology’s true value

Inside the Lab Digital and computational pathology

One Step Beyond: Artificial Intelligence for Image-Based Prognostication

| Nicolas Orsi, Elizabeth Walsh, Katie Allen

Leveraging artificial intelligence for tumor detection and prognostication – and the barriers that stand in the way of adoption

Inside the Lab Digital and computational pathology

Opening Doors to AI-Enabled Pathology

| Talat Zehra

Digitization presents a challenge for low-resource labs – but Talat Zehra offers suggestions that can help them start their digital journey

Diagnostics Digital and computational pathology

Aurora mScope for Microscopy-Based Educators

| Sponsored by Aurora mScope Inc.

An introduction to Aurora mScope’s platform for online microscopy education

Inside the Lab Digital and computational pathology

Aurora Lights Up Cloud-Based Learning

| Erik Yeo

Erik Yeo discusses how Aurora mScope Education was purpose-built for online microscopy education

Outside the Lab Infectious disease

Driving Digitization

| Talat Zehra

Talat Zehra shares her experience of the COVID-19 pandemic

Diagnostics Biochemistry and molecular biology

Putting the Tumor Microenvironment into Spatial Context

| Sponsored by Akoya Biosciences

From bench to bedside, spatial biology can help to guide targeted treatment and predict patient response

Diagnostics Microscopy and imaging

(AI) Skin in the Game

| Michael Schubert

A new convolutional neural network system may lead to faster, easier diagnosis of skin disorders such as epidermolysis bullosa acquisita

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