Machine learning assisted photothermal conversion efficiency prediction of anticancer photothermal agents

Wu, Shijing; Pan, Zhenxing; Li, Xiaojing; Wang, Yan; Tang, Jiacheng; Li, Haishan; Lu, Guibo; Li, Jianzhong; Feng, Zhenzhen; He, Yan; Liu, Xujie

doi:10.1016/j.ces.2023.118619

Cited by 7 publications

(1 citation statement)

References 47 publications

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“…Entre otros métodos menos populares pero que también se han usado para el cálculo de propiedades ópticas en geometrías complejas son el programa de multipolo múltiple (MMP), el método de fuentes auxiliares (MAS), la aproximación de dipolo discreto (DDA), el método de elemento de contorno (BEM), la ecuación integral de contorno sin mallado (MBIE), o métodos de aprendizaje automático (Trügler, 2016;Amirjani and Sadrnezhaad, 2021;Wu et al, 2023).…”

Section: Modelos Y Predicción De Terapias Fototérmicasunclassified

Sistemas Optoelectrónicos para Terapias Fototérmicas Dirigidas al Cáncer de Piel y Optogenética en la Regeneración de Tejido Nervioso

Terrés Haro

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Section: Modelos Y Predicción De Terapias Fototérmicasunclassified

Sistemas Optoelectrónicos para Terapias Fototérmicas Dirigidas al Cáncer de Piel y Optogenética en la Regeneración de Tejido Nervioso

Terrés Haro

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Prediction of ionic liquid surface tension via a generalized interpretable Structure‐Surface Tension Relationship model

Zhu,

Zhang,

Liu

et al. 2024

AIChE Journal

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Ionic liquids' (ILs) surface tension, vital in liquid interface research, faces challenges in measurement methods—time‐consuming and labor‐intensive. The Structure‐Surface Tension Relationship (SSTR) is crucial for understanding the surface tension laws of ionic liquids, helping to predict surface tension and design ionic liquids that meet target requirements. In this study, SMILES string and group contribution methods were used to generate descriptors, and the random forest and multi‐layer perceptron (MLP) models were cross combined with the two descriptor generation methods to establish the SSTR model, providing a comprehensive framework for predicting the surface tension of ionic liquids. String‐MLP excels with high accuracy (R2 = 0.995, RMSE = 0.686, AARD% = 0.71%) for diverse ILs' surface tension values. Meanwhile, the Shapley Additive exPlanning (SHAP) method was used to test the impact of different features on model prediction, increasing the transparency and interpretability of the model.

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Near‐Infrared Nanoparticle‐Mediated Photothermal Cancer Therapy: A Comprehensive Review of Advances in Monitoring and Controlling Thermal Effects for Effective Cancer Treatment

Oudjedi,

Kirk

2024

Nano Select

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Photothermal therapy (PTT) has emerged as a promising alternative to conventional cancer treatments such as radiation therapy, chemotherapy, and surgery. PTT uses light‐absorbing nanomaterials to induce localized hyperthermia and selectively eliminate cancer cells, thus offering advantages over traditional interventions. This literature review focuses on nanoparticles for PTT, their heating properties, and their functions in theragnostic applications for photothermal cancer treatment. It highlights the fundamental principles, recent spectroscopic developments for diagnosis and treatment monitoring, clinical advancements in near‐infrared (NIR) nanoparticle‐mediated PTT, and emerging numerical methods for preclinical planning of PTT.

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Machine learning assisted photothermal conversion efficiency prediction of anticancer photothermal agents

Cited by 7 publications

References 47 publications

Sistemas Optoelectrónicos para Terapias Fototérmicas Dirigidas al Cáncer de Piel y Optogenética en la Regeneración de Tejido Nervioso

Sistemas Optoelectrónicos para Terapias Fototérmicas Dirigidas al Cáncer de Piel y Optogenética en la Regeneración de Tejido Nervioso

Prediction of ionic liquid surface tension via a generalized interpretable Structure‐Surface Tension Relationship model

Near‐Infrared Nanoparticle‐Mediated Photothermal Cancer Therapy: A Comprehensive Review of Advances in Monitoring and Controlling Thermal Effects for Effective Cancer Treatment

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