Diagnostics

JournalCitation impact & published research

Diagnostics is a journal indexed in ScholarIQ from OpenAlex. ScholarIQ records 19,561 works, 230,252 citations, an h-index of 125 and an APC (USD) of 2,227.

19,561

Works

230,252

Citations

125

h-index

2,227

APC (USD)

IDs:OpenAlex

What are the most-cited papers on Diagnostics?

ScholarIQmost cited works

Current and Emerging Methods of Antibiotic Susceptibility Testing

Zeeshan Ahmad Khan, Mohd Farhan Siddiqui, Seungkyung Park

Diagnostics. 2019452 CitationsOPEN ACCESS

Multimodal Brain Tumor Classification Using Deep Learning and Robust Feature Selection: A Machine Learning Application for Radiologists

Muhammad Attique Khan, Imran Ashraf, Majed Alhaisoni, Robertas Damaševičius, Rafał Scherer, Amjad Rehman, Syed Ahmad Chan Bukhari

Diagnostics. 2020424 CitationsOPEN ACCESS

Applications of Explainable Artificial Intelligence in Diagnosis and Surgery

Yiming Zhang, Ying Weng, Jonathan N. Lund

Diagnostics. 2022362 CitationsOPEN ACCESS

Skin Lesion Segmentation and Multiclass Classification Using Deep Learning Features and Improved Moth Flame Optimization

Muhammad Attique Khan, Muhammad Sharif, Tallha Akram, Robertas Damaševičius, Rytis Maskeliūnas

Diagnostics. 2021272 CitationsOPEN ACCESS

Deep Learning Based Automatic Malaria Parasite Detection from Blood Smear and Its Smartphone Based Application

K. M. Faizullah Fuhad, Jannat Ferdousey Tuba, Md. Rabiul Ali Sarker, Sifat Momen, Nabeel Mohammed, Tanzilur Rahman

Diagnostics. 2020184 CitationsOPEN ACCESS

Related on ScholarIQ

Current and Emerging Methods of Antibiotic Susceptibility Testing

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Multimodal Brain Tumor Classification Using Deep Learning and Robust Feature Selection: A Machine Learning Application for Radiologists

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Applications of Explainable Artificial Intelligence in Diagnosis and Surgery

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Skin Lesion Segmentation and Multiclass Classification Using Deep Learning Features and Improved Moth Flame Optimization

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Deep Learning Based Automatic Malaria Parasite Detection from Blood Smear and Its Smartphone Based Application

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Cloud Computing-Based Framework for Breast Cancer Diagnosis Using Extreme Learning Machine

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