Elif Ulutas Deniz, Muhammad Kamran Rasheed, Rumeysa Eren, Hatice Gözeler
Lived experiences of Turkish community pharmacists toward person-centric care: a qualitative analysis
Journal of pharmaceutical policy and practice
imaging mass spectrometry ims provides promising avenues augment histopathological investigation rich spatiomolecular information previously developed classification model differentiate melanoma nevi lesions based ims protein data task challenging solely histopathologic evaluation imsfocused studies collect microscopy tandem ims data microscopy data generally omitted downstream data analysis microscopy nevertheless forms basis traditional histopathology thus contains invaluable morphological information work developed multimodal classification pipeline uses deep learning form pretrained artificial neural network extract meaningful morphological features histopathological images combine ims data test whether deep learningbased classification strategy improve previous results classification melanocytic neoplasia utilized maldi ims data collected serial stained sections 331 patients compared multimodal classification pipeline classifiers using either exclusively microscopy ims data multimodal pipeline achieved best performance rocaucs 0968 vs 0938 vs 0931 multimodal unimodal microscopy unimodal ims pipelines respectively due use pretrained network perform morphological feature extraction pipeline require training large amounts microscopy data framework readily applied improve classification performance experimental settings microscopy data acquired tandem ims experiments