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Chapter and Conference Paper
Self Supervised Contrastive Learning on Multiple Breast Modalities Boosts Classification Performance
Medical imaging classification tasks require models that can provide high accuracy results. Training these models requires large annotated datasets. Such datasets are not openly available, are very costly, and...
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Chapter and Conference Paper
Pre-biopsy Multi-class Classification of Breast Lesion Pathology in Mammograms
Characterization of lesions by artificial intelligence (AI) has been the subject of extensive research. In recent years, many studies demonstrated the ability of convolution neural networks (CNNs) to successfu...
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Chapter and Conference Paper
Learning from Longitudinal Mammography Studies
When reading imaging studies, radiologists often compare the acquired images to one or more prior studies of the patient. Machine learning algorithms that assist in identifying abnormalities in medical images ...
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Chapter and Conference Paper
Distinct Squares in Circular Words
A circular word, or a necklace, is an equivalence class under conjugation of a word. A fundamental question concerning regularities in standard words is bounding the number of distinct squares in a word of len...
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Chapter and Conference Paper
Period Recovery over the Hamming and Edit Distances
A string S of length n has period P of length p if \(S[i]=S[i+p]\) ...
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Article
Open AccessExpaRNA-P: simultaneous exact pattern matching and folding of RNAs
Identifying sequence-structure motifs common to two RNAs can speed up the comparison of structural RNAs substantially. The core algorithm of the existent approach ExpaRNA solves this problem for a priori known in...
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Chapter and Conference Paper
Locating All Maximal Approximate Runs in a String
An exact run in a string, T, is a non-empty substring of T that can be divided into adjacent non-overlap** identical substrings. Finding exact runs in strings is an important problem and therefore a well studie...
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Chapter and Conference Paper
Local Exact Pattern Matching for Non-fixed RNA Structures
Detecting local common sequence-structure regions of RNAs is a biologically meaningful problem. By detecting such regions, biologists are able to identify functional similarity between the inspected molecules....
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Chapter and Conference Paper
Exact Pattern Matching for RNA Structure Ensembles
ExpaRNA’s core algorithm computes, for two fixed RNA structures, a maximal non-overlap** set of maximal exact matchings. We introduce an algorithm ExpaRNA-P that solves the lifted problem of find...
