Applications of QSPR and Machine Learning in Molecular Photonics
Quantitative structureproperty relationships (QSPR) and machine learning (ML) are transforming photochemistry by enabling pre‐synthetic screening of photoactive molecules. This review outlines advances in data‐driven discovery of optical materials and functional dyes, identifies effective descriptors and models for photophysical processes, and provides
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Proteomic and histopathologic profiling reveal molecular features and clinical biomarkers of coronary atherosclerosis. [PDF]
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Pediatric Immunodeficiency Caused by Complement Classical and Alternative Pathway Defects Due to a Homozygous CFI Variant: A Case Report. [PDF]
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Gaps in maternal-fetal interface rejection response: chronic histiocytic intervillositis. [PDF]
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Publisher Correction: Drug-resistant epilepsy associated with peripheral complement decreases and sex-specific cytokine imbalances: a pilot study. [PDF]
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Immunological Targets in Generalized Myasthenia Gravis Treatment: Where Are We Going Now? [PDF]
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