Diagnostic performance for determining malignancy; binary classification. by Seung Seog Han (4782486)

Illustration of unprocessed-image analysis and cropped-image analysis by the algorithm. by Seung Seog Han (4782486)

An example of an OCT image of a DR case (left) and illustration of relevant parts (right): EX-AN blobs (yellow blobs) in the area of interest (a blue region), the ILM (a red line)... by Rinrada Tanthanathewin (18611171)

Melanoma Detection by Means of Multiple Instance Learning by Annabella Astorino (11644324)

“…We present an application to melanoma detection of a multiple instance learning (MIL) approach, whose objective, in the binary case, is to discriminate between positive and negative sets of items. …”

Recognition of each neuron’s digital identity. by Yuxiang Wu (748543)

Performance comparison with the subsets of the Severance Dataset. by Seung Seog Han (4782486)

“…We compared the binary performance of the algorithm with regard to malignancy detection using multiple subsets of the Severance dataset. …”

Dataset selection process and exclusion criteria. by Seung Seog Han (4782486)

Image_1_Validation of miRNA signatures for ovarian cancer earlier detection in the pre-diagnosis setting using machine learning approaches.pdf by Konrad Stawiski (4753380)

PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

“…</p><p><br></p><p dir="ltr">In the fifth measurement technique, the numbers of sharp <b>surface projections/protrusions</b> were calculated by initially applying Canny's edge detection algorithm to generate an edge map of the cell mask image. …”