Muhammad Adam

5.8k total citations · 4 hit papers
27 papers, 4.4k citations indexed

About

Muhammad Adam is a scholar working on Cardiology and Cardiovascular Medicine, Cognitive Neuroscience and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Muhammad Adam has authored 27 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Cardiology and Cardiovascular Medicine, 13 papers in Cognitive Neuroscience and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Muhammad Adam's work include ECG Monitoring and Analysis (18 papers), EEG and Brain-Computer Interfaces (13 papers) and Heart Rate Variability and Autonomic Control (10 papers). Muhammad Adam is often cited by papers focused on ECG Monitoring and Analysis (18 papers), EEG and Brain-Computer Interfaces (13 papers) and Heart Rate Variability and Autonomic Control (10 papers). Muhammad Adam collaborates with scholars based in Singapore, Malaysia and Japan. Muhammad Adam's co-authors include Jen Hong Tan, U. Rajendra Acharya, Yuki Hagiwara, Shu Lih Oh, Hamido Fujita, Ru‐San Tan, Arkadiusz Gertych, Oh Shu Lih, Vidya K. Sudarshan and Chua Kuang Chua and has published in prestigious journals such as IEEE Transactions on Image Processing, Information Sciences and Knowledge-Based Systems.

In The Last Decade

Muhammad Adam

26 papers receiving 4.2k 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.

A deep convolutional neural network model to classify heartbeats

2017 987 citations U. Rajendra Acharya, Shu Lih Oh et al. Computers in Biology and Medicine profile →
Application of deep convolutional neural network for automated detection of myocardial infarction using ECG signals

2017 678 citations U. Rajendra Acharya, Hamido Fujita et al. Information Sciences profile →
Automated detection of arrhythmias using different intervals of tachycardia ECG segments with convolutional neural network

2017 557 citations U. Rajendra Acharya, Hamido Fujita et al. Information Sciences profile →
Application of stacked convolutional and long short-term memory network for accurate identification of CAD ECG signals

2018 289 citations Jen Hong Tan, Yuki Hagiwara et al. Computers in Biology and Medicine profile →

Peers

Muhammad Adam

CCM

PRM

Roshan Joy Martis India

Oliver Faust Singapore

Elif Derya Übeylï Türkiye

Samarendra Dandapat India

S. Vinitha Sree Singapore

Vidya K. Sudarshan Singapore

İnan Güler Türkiye

Oh Shu Lih Singapore

Rajesh Kumar Tripathy India

Joel E.W. Koh Singapore

Roshan Joy Martis India

Muhammad Adam

2.6k ×0.8

CCM

2.6k ×1.2

902 ×0.8

530 ×0.8

PRM

492 ×1.0

Citations per year, relative to Muhammad Adam Muhammad Adam (= 1×) peers Roshan Joy Martis

Countries citing papers authored by Muhammad Adam

Since Specialization

Citations

This map shows the geographic impact of Muhammad Adam'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 Muhammad Adam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Adam more than expected).

Fields of papers citing papers by Muhammad Adam

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Muhammad Adam. 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 Muhammad Adam. The network helps show where Muhammad Adam may publish in the future.

Co-authorship network of co-authors of Muhammad Adam

This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Adam. A scholar is included among the top collaborators of Muhammad Adam 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 Muhammad Adam. Muhammad Adam is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Adam, Muhammad, et al.. (2025). Deep Learning Approaches for Automatic Livestock Detection in UAV Imagery: State-of-the-Art and Future Directions. Future Internet. 17(9). 431–431.

Adam, Muhammad, et al.. (2020). Rancang Bangun Aplikasi PHP dalam Mendeteksi Penyakit Kelinci Menggunakan Metode Case-Based Reasoning (CBR). Journal of Computer System and Informatics (JoSYC). 1(4). 293–302. 1 indexed citations

Adam, Muhammad, Shu Lih Oh, Vidya K. Sudarshan, et al.. (2018). Automated characterization of cardiovascular diseases using relative wavelet nonlinear features extracted from ECG signals. Computer Methods and Programs in Biomedicine. 161. 133–143. 43 indexed citations

Tan, Jen Hong, Yuki Hagiwara, Ivy Lim, et al.. (2018). Application of stacked convolutional and long short-term memory network for accurate identification of CAD ECG signals. Computers in Biology and Medicine. 94. 19–26. 289 indexed citations breakdown →

Acharya, U. Rajendra, Hamido Fujita, Shu Lih Oh, et al.. (2018). Deep convolutional neural network for the automated diagnosis of congestive heart failure using ECG signals. Applied Intelligence. 49(1). 16–27. 222 indexed citations

Acharya, U. Rajendra, Yuki Hagiwara, Joel E.W. Koh, et al.. (2018). Entropies for automated detection of coronary artery disease using ECG signals: A review. Journal of Applied Biomedicine. 38(2). 373–384. 92 indexed citations

Adam, Muhammad, E. Y. K. Ng, Shu Lih Oh, et al.. (2018). Automated characterization of diabetic foot using nonlinear features extracted from thermograms. Infrared Physics & Technology. 89. 325–337. 40 indexed citations

Adam, Muhammad, Jen Hong Tan, & E. Y. K. Ng. (2017). THE EFFECT OF DIABETES ON CARDIOVASCULAR SYSTEM. Journal of Mechanics in Medicine and Biology. 17(7). 1740008–1740008. 2 indexed citations

Sudarshan, Vidya K., U. Rajendra Acharya, Shu Lih Oh, et al.. (2017). Automated diagnosis of congestive heart failure using dual tree complex wavelet transform and statistical features extracted from 2 s of ECG signals. Computers in Biology and Medicine. 83. 48–58. 67 indexed citations

10.

Acharya, U. Rajendra, Hamido Fujita, Shu Lih Oh, et al.. (2017). Application of deep convolutional neural network for automated detection of myocardial infarction using ECG signals. Information Sciences. 415-416. 190–198. 678 indexed citations breakdown →

11.

Adam, Muhammad, et al.. (2017). Computer aided diagnosis of diabetic foot using infrared thermography: A review. Computers in Biology and Medicine. 91. 326–336. 70 indexed citations

12.

Adam, Muhammad, et al.. (2017). Early Detection of Breast Cancer by Using Handycam Camera Manipulation as Thermal Camera Imaging with Images Processing Method. IOP Conference Series Materials Science and Engineering. 176. 12021–12021. 1 indexed citations

13.

Acharya, U. Rajendra, Shu Lih Oh, Yuki Hagiwara, et al.. (2017). A deep convolutional neural network model to classify heartbeats. Computers in Biology and Medicine. 89. 389–396. 987 indexed citations breakdown →

14.

Acharya, U. Rajendra, Hamido Fujita, Oh Shu Lih, et al.. (2017). Automated detection of arrhythmias using different intervals of tachycardia ECG segments with convolutional neural network. Information Sciences. 405. 81–90. 557 indexed citations breakdown →

15.

Acharya, U. Rajendra, Hamido Fujita, Oh Shu Lih, et al.. (2017). Automated detection of coronary artery disease using different durations of ECG segments with convolutional neural network. Knowledge-Based Systems. 132. 62–71. 281 indexed citations

16.

Acharya, U. Rajendra, Hamido Fujita, Vidya K. Sudarshan, et al.. (2017). Automated characterization of coronary artery disease, myocardial infarction, and congestive heart failure using contourlet and shearlet transforms of electrocardiogram signal. Knowledge-Based Systems. 132. 156–166. 79 indexed citations

17.

Oh, Shu Lih, Yuki Hagiwara, Muhammad Adam, et al.. (2017). SHOCKABLE VERSUS NONSHOCKABLE LIFE-THREATENING VENTRICULAR ARRHYTHMIAS USING DWT AND NONLINEAR FEATURES OF ECG SIGNALS. Journal of Mechanics in Medicine and Biology. 17(7). 1740004–1740004. 13 indexed citations

18.

Acharya, U. Rajendra, Hamido Fujita, Muhammad Adam, et al.. (2016). Automated characterization and classification of coronary artery disease and myocardial infarction by decomposition of ECG signals: A comparative study. Information Sciences. 377. 17–29. 193 indexed citations

19.

Acharya, U. Rajendra, Hamido Fujita, Vidya K. Sudarshan, et al.. (2016). Automated detection and localization of myocardial infarction using electrocardiogram: a comparative study of different leads. Knowledge-Based Systems. 99. 146–156. 199 indexed citations

20.

Adam, Muhammad, et al.. (2000). Reversible integer-to-integer wavelet transforms for image compression: performance evaluation and analysis. IEEE Transactions on Image Processing. 9(6). 1010–1024. 261 indexed citations

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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