Michael Mian

78 papers receiving 1.1k citations

Michael Mian's Hit Papers

Human intelligence versus Chat-GPT: who performs better in correctly classifying patients in triage? 2024 · 46 citations
460+1Years since publication10203040

Peers

Michael Mian
Comparison fields: 5 of 102
  • Pathology and Forensic Medicine 517
  • Genetics 260
  • Health Informatics 32
  • Urology 103
  • Oncology 353
Replace Ewald Wöll with:
Ewald Wöll Austria
Amy M. DeLozier United States
Sławomir Jeka Poland
Bo Xiang China
Chiara Crotti Italy
Luís Meza United States
Hongqing Zhuang China
Mohsen Ibrahim Italy
B. L. Hazleman United Kingdom
Michael Mian relative to Ewald Wöll Austria Ewald Wöll's profile →
Citations per field
00.5×6.3×
Ewald Wöll · 1×
Citations per year

Countries citing papers authored by Michael Mian

Since Specialization
Citations

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

Fields of papers citing papers by Michael Mian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Michael Mian, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Mian Line = papers co-authored together Michael Mian links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201574
2 201474
3 200864
4 201051
5 201446
6
Human intelligence versus Chat-GPT: who performs better in correctly classifying patients in triage?
Hit paper breakdown →
202446
7 201942
8 200937
9
The value of the ImmunoCyt/uCyt+ test in the detection and follow-up of carcinoma in situ of the urinary bladder.
200536
10 201234
11 201330
12 201427
13 201027
14 201727
15 201627
16 201125
17 201024
18 201524
19 201023
20 201622

About Michael Mian

Michael Mian is a scholar working on Pathology and Forensic Medicine, Oncology, Genetics, Neurology and Pulmonary and Respiratory Medicine, having authored 82 papers that have together received 1.1k indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (40 papers), Chronic Lymphocytic Leukemia Research (15 papers), CNS Lymphoma Diagnosis and Treatment (13 papers), Viral-associated cancers and disorders (11 papers), Emergency and Acute Care Studies (10 papers), Bladder and Urothelial Cancer Treatments (6 papers), Trauma and Emergency Care Studies (5 papers) and Urinary and Genital Oncology Studies (5 papers). The work is most often cited by research in Pathology and Forensic Medicine (517 citations), Genetics (260 citations), Health Informatics (32 citations), Urology (103 citations) and Oncology (353 citations). Michael Mian has collaborated with scholars based in Italy, Austria and United States. Frequent co-authors include Patrizia Mondello, Salvatore Cuzzocrea, Armin Pycha, Vincenzo Pitini, Christine Mian, Evi Comploj, Salvatore Palermo, Michele Lodde, Michael Fiegl and Francesco Bertoni. Their work appears in journals such as Blood, Annals of Hematology, Annals of Oncology, Internal and Emergency Medicine and British Journal of Haematology.

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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