Applications can be submitted here at any time. They are reviewed and accepted in cycles. The current cycle is running until April 20th, so send in your application any time before April 20th.
Applications will be reviewed by an independent Advisory Team. Qualified projects will be selected and invited to join the program. The current cycle of applicants will receive a response beginning of May.
3. AI Implementation
Selected projects will be assigned a dedicated program manager and support from a team of AI experts.
The best projects will be awarded annually.
You can apply here at any time. Applications will be reviewed by an independent advisory team composed of researchers and medical and AI experts. Qualified projects will be selected and invited to join the program.
aiForward welcomes projects of many kinds, and every application will be reviewed individually. The holistic evaluation process considers the feasibility of AI in the project and its potential scientific impact. Those projects with a timeline utilizing artificial intelligence in the near future are given priority.
A good fit within the given categories (cancer, neurology, infectious diseases, and lifestyle diseases) is also considered a plus. However, exceptional projects beyond these categories may also be accepted.
Every applicant will be contacted via email or phone at the time of application review.
Applications are reviewed and accepted in cycles. The current cycle is running until April 20th meaning you can send in your application any time before April 20th, it will then be reviewed and you will receive a response beginning of May. The next cycle will then be announced shortly afterwards.
How soon can I start the project after my application has been accepted? How long does the program last?
The schedule will be planned individually for each project based on the project’s current status. Image analysis should be conducted within one year after the project gets admitted to aiForward.
The Advisory Team consists of independent experts in AI, pathology, and the primary focus areas (cancer, neurology, infectious diseases, and lifestyle diseases). Each quarter the Advisory Team will perform reviews and select projects based on applications. During the program, the Advisory Team will advise participants regarding selected questions in their areas of expertise. The Advisory team will also select the top projects to be awarded annually.
The time required for AI-implementation depends on the project, samples, and complexity of the image analysis task. Annotating the features of interest in the sample images requires some effort and hands-on work from the participant. The time needed will be estimated together with the participants at the onset of the program.
aiForward participants get free access to the Aiforia® Create tool, which is compatible with the following 2D scanner file formats:
- Hamamatsu: .ndpi, .vms
- Leica-Aperio: .scn, .svs
- PerkinElmer: .qptiff
- Philips: .tif
- 3DHistech: .mrxs
The following image file formats are also compatible with Aiforia Create:
- JPEG2000: .jp2, .jpf, .jpx, .ecw
- TIFF: .tiff, .tif
- Other: .bmp, .jpeg, .jpg, .jpe, .png
You can indicate this in your application. If your project gets selected, aiForward will help you with the scanning.
All intellectual property rights to the glass slides and sample images scanned by an aiForward participant will remain the exclusive property of the participant. Aiforia is entitled to use the slide images only within the scope of the selected project.
How long can participants continue using for free the algorithm created during the aiForward program?
The algorithm is available within the scope and timeframe of your approved project. To use the algorithm beyond the agreed purposes and time period, you can sign up for an Aiforia subscription.
aiForward and Aiforia can disclose participants’ name, organization, research area, and application of AI in selected research projects, as illustrated in the fictional example below.
Dr. Raj Patel studies HER2+ positive breast cancer at the St. Elsewhere hospital. His research group applies AI to improve the accuracy and efficiency of whole slide image analysis. With a dataset of around 100 research samples, Dr. Patel is aiming to train deep learning AI algorithms to recognize the characteristic staining patterns in membrane regions.
“An algorithm that provides consistent analysis with less hands-on work would be a powerful grading and classification tool for breast cancer research,” says Dr. Patel.
Few selected participants will be invited to share voluntary information on the progress of their project for documentary purposes. aiForward does not disclose research plans, results or discoveries without permission.