Toktam Khatibi

734 total citations · 1 hit paper
41 papers, 474 citations indexed

About

Toktam Khatibi is a scholar working on Computer Vision and Pattern Recognition, Oncology and Artificial Intelligence. According to data from OpenAlex, Toktam Khatibi has authored 41 papers receiving a total of 474 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 7 papers in Oncology and 7 papers in Artificial Intelligence. Recurrent topics in Toktam Khatibi's work include Colorectal Cancer Screening and Detection (4 papers), Digital Imaging for Blood Diseases (3 papers) and Healthcare Operations and Scheduling Optimization (3 papers). Toktam Khatibi is often cited by papers focused on Colorectal Cancer Screening and Detection (4 papers), Digital Imaging for Blood Diseases (3 papers) and Healthcare Operations and Scheduling Optimization (3 papers). Toktam Khatibi collaborates with scholars based in Iran, United States and Canada. Toktam Khatibi's co-authors include Mohammad Mehdi Sepehri, Mehdi Totonchi, Ali Shahsavari, Firouzeh Ghaffari, Azim Mehrvar, Shadi Shafaghi, Seyed Alireza Mahdaviani, Leila Allahqoli, Masoudreza Sohrabi and Saeed Parsa and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Cleaner Production.

In The Last Decade

Toktam Khatibi

39 papers receiving 463 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

CNFE-SE: a novel approach combining complex network-based feature engineering and stacked ensemble to predict the success of intrauterine insemination and ranking the features

2021 115 citations Toktam Khatibi, Mehdi Totonchi et al. BMC Medical Informatics and Decision Making profile →

Peers

Countries citing papers authored by Toktam Khatibi

Since Specialization

Citations

This map shows the geographic impact of Toktam Khatibi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Toktam Khatibi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Toktam Khatibi more than expected).

Fields of papers citing papers by Toktam Khatibi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Toktam Khatibi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Toktam Khatibi. The network helps show where Toktam Khatibi may publish in the future.

Co-authorship network of co-authors of Toktam Khatibi

This figure shows the co-authorship network connecting the top 25 collaborators of Toktam Khatibi. A scholar is included among the top collaborators of Toktam Khatibi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Toktam Khatibi. Toktam Khatibi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Proposing a model based on deep reinforcement learning for real-time scheduling of collaborative customization remanufacturing 2025 ·Robotics and Computer-Integrated Manufacturing ·(unknown), Seyed Hessameddin Zegordi, Toktam Khatibi	1
2	Revolutionizing sleep disorder diagnosis: A Multi-Task learning approach optimized with genetic and Q-Learning techniques 2025 ·Scientific Reports ·(unknown), Toktam Khatibi, (unknown), (unknown), (unknown)	0
3	Optimizing Emergency Department Resource Allocation Using Discrete Event Simulation and Machine Learning Techniques 2024 ·(unknown), (unknown), Toktam Khatibi	0
4	Personalised emotion-aware e-learning systems with interventions 2023 ·(unknown), Mohammad Mehdi Sepehri, Soheil Sibdari, Toktam Khatibi, Hassan Aghajani	1
5	Student performance prediction using datamining classification algorithms: Evaluating generalizability of models from geographical aspect 2023 ·Education and Information Technologies ·(unknown), (unknown), Toktam Khatibi	4
6	Combining CNNs and 2-D visualization method for GI tract lesions classification 2023 ·Multimedia Tools and Applications ·(unknown), Toktam Khatibi, Masoudreza Sohrabi	2
7	Proposing a two-step decision support system for differential diagnosis of tuberculosis from pneumonia 2022 ·SHILAP Revista de lepidopterología ·(unknown), Toktam Khatibi, (unknown), Azam Boskabadi	2
8	Proposing a novel multi-instance learning model for tuberculosis recognition from chest X-ray images based on CNNs, complex networks and stacked ensemble 2021 ·Physical and Engineering Sciences in Medicine ·Toktam Khatibi, Ali Shahsavari, (unknown)	29
9	CNFE-SE: a novel approach combining complex network-based feature engineering and stacked ensemble to predict the success of intrauterine insemination and ranking the features breakdown → 2021 ·BMC Medical Informatics and Decision Making ·(unknown), Toktam Khatibi, (unknown), (unknown), Mehdi Totonchi, Firouzeh Ghaffari	115
10	Development of glaucoma predictive model and risk factors assessment based on supervised models 2021 ·BioData Mining ·(unknown), Toktam Khatibi, Mohammad Hassan Emamian, (unknown), Hassan Hashemi, Akbar Fotouhi	4
11	Proposing a machine-learning based method to predict stillbirth before and during delivery and ranking the features: nationwide retrospective cross-sectional study 2021 ·BMC Pregnancy and Childbirth ·Toktam Khatibi, (unknown), Mohammad Mehdi Sepehri, Leila Allahqoli	13
12	Prediction of Cranial Radiotherapy Treatment in Pediatric Acute Lymphoblastic Leukemia Patients Using Machine Learning: A Case Study at MAHAK Hospital 2020 ·Asian Pacific Journal of Cancer Prevention ·(unknown), Toktam Khatibi, Azim Mehrvar	13
13	An intelligent warning model for early prediction of cardiac arrest in sepsis patients 2019 ·Computer Methods and Programs in Biomedicine ·(unknown), Mohammad Mehdi Sepehri, (unknown), Toktam Khatibi	59
14	Proposing feature engineering method based on deep learning and K-NNs for ECG beat classification and arrhythmia detection 2019 ·Physical and Engineering Sciences in Medicine ·Toktam Khatibi, (unknown)	22
15	Identification and weighting of kidney allocation criteria: a novel multi-expert fuzzy method 2019 ·BMC Medical Informatics and Decision Making ·(unknown), Mohammad Mehdi Sepehri, Shadi Shafaghi, Toktam Khatibi	16
16	Analysis of big data for prediction of provider-initiated preterm birth and spontaneous premature deliveries and ranking the predictive features 2019 ·Archives of Gynecology and Obstetrics ·Toktam Khatibi, (unknown), Mohammad Mehdi Sepehri	24
17	An analytical model based on simulation aiming to improve patient flow in a hospital surgical suite 2018 ·Journal of industrial and systems engineering. ·(unknown), Mohammad Mehdi Sepehri, Toktam Khatibi	2
18	Extraction and Comparison of the Discharge Process in a Teaching Hospital 2017 ·Toktam Khatibi, (unknown)	1
19	Selecting Differentiated Costs between primary PCI and Thrombolytic Therapy using Hybrid of Genetic Algorithm and Decision Tree Approach 2015 ·SHILAP Revista de lepidopterología ·(unknown), (unknown), Hassan Aghajani, Toktam Khatibi	1
20	A Fuzzy FMEA Approach to Prioritizing Surgical Cancellation Factors 2013 ·(unknown), Mohammad Mehdi Sepehri, Toktam Khatibi	12

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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