Review
Biology
Zohaib Salahuddin, Henry C. Woodruff, Avishek Chatterjee, Philippe Lambin
Summary: AI is increasingly used in clinical applications for diagnosis and treatment decisions, with deep neural networks showing equal or better performance than clinicians. However, their lack of interpretability calls for the development of methods to ensure their trustworthiness. Nine different types of interpretability methods have been identified for understanding deep learning models in medical image analysis, with ongoing research on improving interpretability and evaluation methods for deep neural networks.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Multidisciplinary Sciences
Tao Yan, Rui Yang, Ziyang Zheng, Xing Lin, Hongkai Xiong, Qionghai Dai
Summary: Photonic neural networks use photons instead of electrons to perform brain-like computations, leading to significantly improved computing performance. However, current architectures are limited to handling data with regular structures and cannot generalize to graph-structured data beyond Euclidean space. In this study, a diffractive graph neural network (DGNN) is proposed to address this limitation by utilizing diffractive photonic computing units (DPUs) and on-chip optical devices. DGNN achieves complex feature representation by capturing dependencies among node neighborhoods during light-speed optical message passing over graph structures. It demonstrates superior performance in node and graph-level classification tasks with benchmark databases, providing a new direction for high-efficiency processing of large-scale graph data structures using deep learning.
Review
Pharmacology & Pharmacy
Carmen Cerchia, Antonio Lavecchia
Summary: In the past decade, the availability of biomedical data has grown rapidly. Machine learning and artificial intelligence techniques have been widely used to mine these data and extract useful patterns. These technologies have the potential to accelerate drug discovery and support decision making.
DRUG DISCOVERY TODAY
(2023)
Review
Chemistry, Multidisciplinary
Konstantinos D. Stergiou, Georgios M. Minopoulos, Vasileios A. Memos, Christos L. Stergiou, Maria P. Koidou, Konstantinos E. Psannis
Summary: This paper discusses the combination of Internet of Things and cloud computing with AI, ML, DL, and NN, providing a useful approach for scientists and doctors in terms of epidemic forecasting and accelerating drug and antibiotic discovery.
APPLIED SCIENCES-BASEL
(2022)
Review
Pharmacology & Pharmacy
Sundaravadivelu Sumathi, Kanagaraj Suganya, Kandasamy Swathi, Balraj Sudha, Arumugam Poornima, Chalos Angel Varghese, Raghu Aswathy
Summary: The use of artificial intelligence, particularly deep learning, in drug discovery has significantly accelerated the research and development process, exceeding expectations and showing promise in various areas.
CURRENT PHARMACEUTICAL DESIGN
(2023)
Article
Chemistry, Multidisciplinary
JiHwan Lee, Seok Won Chung
Summary: Deep learning has been rapidly integrated into the field of medicine, specifically in orthopedics, showing outstanding performance in diagnosis. However, there are still areas, such as segmentation and prediction, that require further improvement. This review provides orthopedic surgeons with an overall understanding of artificial intelligence-based image analysis, while also discussing future directions for research in this field.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Artificial Intelligence
Bas H. M. Van der Velden, Hugo J. Kuijf, Kenneth G. A. Gilhuijs, Max A. Viergever
Summary: This survey examines the applications of explainable artificial intelligence (XAI) in deep learning-based medical image analysis. It introduces a framework for classifying deep learning-based medical image analysis methods based on XAI criteria. The survey also categorizes and investigates XAI techniques in medical image analysis according to the framework and anatomical location. The paper concludes by discussing future opportunities for XAI in medical image analysis.
MEDICAL IMAGE ANALYSIS
(2022)
Review
Pharmacology & Pharmacy
R. S. K. Vijayan, Jan Kihlberg, Jason B. Cross, Vasanthanathan Poongavanam
Summary: Artificial intelligence is playing a crucial role in drug discovery, from target identification to preclinical development. This review provides an overview of current AI technologies and presents real impact examples, while discussing the opportunities and challenges of adopting AI in drug discovery.
DRUG DISCOVERY TODAY
(2022)
Article
Computer Science, Artificial Intelligence
Leander Weber, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek
Summary: Explainable Artificial Intelligence (XAI) is a research field that aims to bring transparency to complex and opaque machine learning models. This paper provides an overview of techniques that practically apply XAI to improve ML models, categorizing and comparing their strengths and weaknesses. Theoretical perspectives and empirical experiments demonstrate how explanations can enhance properties such as model generalization and reasoning. The potential caveats and drawbacks of these methods are also discussed.
INFORMATION FUSION
(2023)
Article
Chemistry, Multidisciplinary
Martin Kraeter, Shada Abuhattum, Despina Soteriou, Angela Jacobi, Thomas Krueger, Jochen Guck, Maik Herbig
Summary: AID is an easy-to-use, adaptable, and open source software for training neural networks for image classification without the need for programming. It allows for a variety of neural network architectures, benchmarking on large image datasets, and interdisciplinary use by non-programmers on generic computers.
Review
Surgery
Roi Anteby, Nir Horesh, Shelly Soffer, Yaniv Zager, Yiftach Barash, Imri Amiel, Danny Rosin, Mordechai Gutman, Eyal Klang
Summary: The study evaluated the accuracy of deep learning networks in analyzing laparoscopic surgery videos, showing applications mainly in surgery or instrument recognition, phase recognition, and anatomy recognition. Deep learning holds potential in laparoscopic surgery, but is limited by methodologies.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
(2021)
Article
Computer Science, Artificial Intelligence
Michela Proietti, Alessio Ragno, Biagio La Rosa, Rino Ragno, Roberto Capobianco
Summary: In this work, concept whitening is applied to graph neural networks to improve both classification performance and interpretability. By identifying key concepts and structural parts of molecules, explanations are provided for the predictions.
Review
Oncology
Xiaoyan Jiang, Zuojin Hu, Shuihua Wang, Yudong Zhang
Summary: This article provides a detailed overview of the working mechanisms and use cases of deep learning in medical image-based cancer diagnosis. It discusses the basic architecture of deep learning, pretrained models, methods to overcome overfitting, and the application of deep learning in cancer diagnosis. The article also explores the challenges and future research directions in this field.
Review
Biology
Arash Heidari, Nima Jafari Navimipour, Mehmet Unal, Shiva Toumaj
Summary: The COVID-19 outbreak has caused significant harm to human existence, but the application of deep learning in the medical field provides effective tools for combating the pandemic. This study utilizes a systematic literature review approach to summarize the latest research on deep learning techniques for COVID-19 related problems, while addressing various issues and challenges associated with implementing deep learning.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Review
Computer Science, Hardware & Architecture
Jian Wang, Hengde Zhu, Shui-Hua Wang, Yu-Dong Zhang
Summary: Transfer learning is gaining popularity in medical image processing due to its efficiency and cost-effectiveness. Despite the variety of medical imaging methods available, labeling data remains a challenge, making transfer learning a valuable solution. Research on the application of transfer learning in medical image analysis holds significant importance for the future development of the field.
MOBILE NETWORKS & APPLICATIONS
(2021)
Article
Neurosciences
Hyun-Jong Jang, Joo Youn Kim, Seong Yun Kim, Kyung-Ok Cho
MOLECULAR NEUROBIOLOGY
(2019)
Article
Biochemistry & Molecular Biology
Hyun-Jong Jang, Ji-Eun Kim, Kyoung Hoon Jeong, Sung Chul Lim, Seong Yun Kim, Kyung-Ok Cho
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2019)
Article
Multidisciplinary Sciences
Kyung-Ok Cho, Hyun-Jong Jang
SCIENTIFIC REPORTS
(2020)
Article
Multidisciplinary Sciences
Kwang-Mo Park, Ji-Eun Kim, In-Young Choi, Kyung-Ok Cho
JOVE-JOURNAL OF VISUALIZED EXPERIMENTS
(2020)
Article
Neurosciences
Kyoung Hoon Jeong, Kyung-Ok Cho, Mun-Yong Lee, Seong Yun Kim, Won-Joo Kim
Summary: The study reveals that VEGFR-3-mediated mTOR activation may contribute to regulating GLT-1 expression in reactive astrocytes during the subacute phase of epilepsy. Upregulation of VEGFR-3 in reactive astrocytes may play a role in preventing hyperexcitability induced by continued seizure activity.
Article
Multidisciplinary Sciences
Zane R. Lybrand, Sonal Goswami, Jingfei Zhu, Veronica Jarzabek, Nikolas Merlock, Mahafuza Aktar, Courtney Smith, Ling Zhang, Parul Varma, Kyung-Ok Cho, Shaoyu Ge, Jenny Hsieh
Summary: In this study, researchers identified a critical window of activity associated with the aberrant maturation of adult-born granule cells (abGCs) in the mammalian hippocampus, which contributes to epileptogenesis. Silencing aberrant abGCs during this critical period reduced abnormal dendrite morphology, cell migration, and seizures in a mouse model of temporal lobe epilepsy. Furthermore, the study demonstrated that GABA-mediated amplification of intracellular calcium regulates the early critical period of activity.
NATURE COMMUNICATIONS
(2021)
Article
Neurosciences
In-Young Choi, Jae Hyuk Shim, Mi-Hye Kim, Won Dong Yu, Yu Jin Kim, Gain Choi, Jae Ho Lee, Hee Jung Kim, Kyung-Ok Cho
Summary: During seizure-induced hippocampal necroptosis, an increase in truncated neogenin levels and a decrease in full-length neogenin levels were observed, along with an upregulation of phosphorylation of mixed lineage kinase domain-like pseudokinase. Treatment with DAPT can prevent neogenin truncation and protect neurons from NMDA-induced death.
Correction
Pharmacology & Pharmacy
Kyung-Eon Lee, Seul-Ki Kim, Kyung-Ok Cho, Seong Yun Kim
KOREAN JOURNAL OF PHYSIOLOGY & PHARMACOLOGY
(2022)
Article
Neurosciences
In-Young Choi, Mi-La Cho, Kyung-Ok Cho
Summary: In this study, researchers identified a novel target, interleukin-17A (IL-17A), which may contribute to anxiety in temporal lobe epilepsy (TLE). By deleting the IL-17A gene, they were able to alleviate TLE-associated anxiety behavior and reduce seizure-induced aberrant neurogenesis.
FRONTIERS IN MOLECULAR NEUROSCIENCE
(2022)
Editorial Material
Neurosciences
Daniel A. Berg, Kyung-Ok Cho, Mi-Hyeon Jang
FRONTIERS IN MOLECULAR NEUROSCIENCE
(2022)
Article
Medicine, Research & Experimental
Hyun Gi Kim, Dongyeob Han, Jimin Kim, Jeong-Sun Choi, Kyung-Ok Cho
Summary: This study investigated the potential of Magnetic Resonance Fingerprinting (MRF) as a noninvasive method for quantifying brain myelin content. The study found associations between MRF-derived myelin water fraction (MWF) and histological myelin quantity, age, and the presence of leukodystrophy in both mice and humans. These findings highlight the potential applicability of MRF-derived MWF in assessing brain development and disease.
JOURNAL OF TRANSLATIONAL MEDICINE
(2023)
Article
Biochemistry & Molecular Biology
Gyung-Ah Jung, Jin-A Kim, Hwan-Woo Park, Hyemi Lee, Mi-Sook Chang, Kyung-Ok Cho, Byeong-Wook Song, Hyun-Ju Kim, Yunhee Kim Kwon, Il-Hoan Oh
Summary: This study reveals the crucial role of NANOG regulatory protein in neuronal regeneration after ischemic stroke, showing its induction can promote the expansion of neuronal cells and regeneration of brain tissue, suggesting cellular plasticity as a potential link between regeneration and reprogramming processes.
EXPERIMENTAL AND MOLECULAR MEDICINE
(2022)
Review
Urology & Nephrology
Ja Un Moon, Kyung-Ok Cho
Summary: Epileptic encephalopathy is a devastating pediatric disease characterized by medically resistant seizures and global developmental delays, with limited therapeutic options due to incomplete understanding of its neurobiological mechanisms. Common EEs in pediatrics include Ohtahara syndrome, Dravet syndrome, and Lennox-Gastaut syndrome, with molecular mechanisms involving dysregulation of ion channels and synaptic transmission-related proteins. Further research is needed to explore these mechanisms and develop new drugs for patients with intractable epilepsy.
INTERNATIONAL NEUROUROLOGY JOURNAL
(2021)
Article
Pharmacology & Pharmacy
Kyung-Ok Cho, Kyoung Hoon Jeong, Jung-Ho Cha, Seong Yun Kim
KOREAN JOURNAL OF PHYSIOLOGY & PHARMACOLOGY
(2020)
Article
Pharmacology & Pharmacy
Hyun-Jong Jang, Kyung-Ok Cho
KOREAN JOURNAL OF PHYSIOLOGY & PHARMACOLOGY
(2019)