Aiforia use cases by application

Creation of an AI model to quantify and localize Clever-1 protein in the tumor microenvironment at Faron Pharmaceuticals.

Automated calculation and scoring of PD-L1 markers in a lung at Leiden University Medical Centre.

Calculating Ki-67 proliferation index for pulmonary carcinoid tumors with AI at the Helsinki University Hospital.

Creation of AI model to accurately classify high grade serous carcinoma into outcome groups at the University of Helsinki.

AI-assisted segmentation of colorectal carcinoma digitized images to identify prognostic and predictive histologic signatures at Mayo Clinic.

AI assisted detection of IHC stained CD3+ T-cells, CD20+ B-cells, DC-Lamp+ mature dendritic cells, and Hematoxylin in a HER2+ breast cancer surgical resection at the Royal College of Surgeons in Ireland.

AI trained to identify blast cells and red blood cells on previously diagnosed cases of acute myelogenous leukemia at the Jinnah Sindh Medical University.

Automating tumor grading in non-small cell lung cancer (NSCLC) studies at MIT.

Automated tumor grading in prostate cancer biopsies at the Helsinki University Hospital, Finland, and in Region Skåne lab, Sweden.

Automated tumor grading in breast cancer biopsies.

Mitosis detection and quantification.

Identifying novel prognostic biomarkers in primary sclerosing cholangitis (PSC) at the Helsinki University Hospital.

AI in studying nonalcoholic fatty liver disease (NAFLD) and its capability to segment structures in liver histology at the University of Helsinki.

Automated quantification of damage and scarring in liver tissue in nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH).

Automated quantification of inflammation in liver tissue in nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH).

Automated quantification of fat accumulation in liver tissue in nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH).

AI model used to identify and enumerate hematopoietic cells to determine changes in bone marrow cellularity for pharmacologic safety studies at Charles River Laboratories.

Using AI for detecting the cortex and medulla and reviewing tissues for histopathological lesions in blinded studies at Texas A&M University.

DSS-induced colitis AI model trained for histopathological lesion detection and colon inflammation assessments at Charles River Laboratories.

Automated malaria parasite detection from blood smears at the University of Helsinki.

Automated detection and quantification of cells and lesions in tuberculosis studies at Tufts University.

Identification and quantification of histopathological features of idiopathic pulmonary fibrosis (IPF) including fibroblast foci, and interstitial and alveolar inflammatory cells at the University of Helsinki.

Neovascular lesion identification in SD-OCT scans for preclinical model development with the contract research organization Experimentica.

Analyzing microscopic images of human blood and tissue to identify patterns of COVID-related disease at the Foundation for the Study of Inflammatory Disease.

Charles River Laboratories pathologists are enhancing image analysis in pre-clinical toxicology, lung studies for lung tissue detection, parenchyma, structural collagen, and fibrotic lesions.

Quantification of HLA-G/CK7 ratios for protein expression in preeclampsia research at Helsinki University Hospital.

Automated segmentation and quantification of endometrial leukocytes and proliferation in PCOS with immunohistochemically stained endometrial samples.

AI-assisted image analysis of cytological samples from mice to determine the stages of the estrus cycle at the University of Turku.

Multichannel (Immunofluorescence) human colon tissue showing staining for various vascular and immune cell markers in addition to epithelium.

Aiforia Create training window showing annotations for NICD1 protein in multi-channel (Immunofluorescence) human colon tissue, stained with various vascular & immune cell markers in addition to epithelium.

Automated detection of dermis and epidermis of skin tissue sample.

Automated white blood cell (WBC) count in a blood samples.

Acute respiratory distress syndrome (ARDS) lesion segmentation and cell identification.

Automated detection of intact yeast cells in bright field images.

AI-aided identification of contamination in yeast fermentations.

Scientists at Nofima used AI to recognize and analyze the successive tissues in Atlantic salmon skin for food safety studies.

Whole image instance segmentation of barley, including identification of protein matrix, starch, and cell wall. 

Measuring concrete porosity and composition.