In–Ho Cha

4.4k citations
175 papers · 3.2k indexed · 1 hit paper · h-index 31

Impact in

Papers in

In–Ho Cha

155 papers receiving 3.1k citations

Hit Papers

Deep learning-based survival prediction of oral cancer patients 2019 · 219 citations
219201920262021202350100150200

Peers

In–Ho Cha
Comparison fields: 5 of 148
  • Otorhinolaryngology 429
  • Oral Surgery 647
  • Health Informatics 63
  • Periodontics 179
  • Orthopedics and Sports Medicine 243
Replace Aline Carvalho Batista with:
Aline Carvalho Batista Brazil
Giuseppe Troiano Italy
Hitoshi Yoshimura Japan
Corrado Rubini Italy
Yue Chen China
Pratibha Ramani India
Kyung Soo Chung South Korea
Xi Chen China
Hui Chen China
Eiichi Sato Japan
In–Ho Cha relative to Aline Carvalho Batista Brazil Aline Carvalho Batista's profile →
Citations per field
00.5×7.8×
Aline Carvalho Batista · 1×
Citations per year

Countries citing papers authored by In–Ho Cha

Since Specialization
Citations

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

Fields of papers citing papers by In–Ho Cha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by In–Ho Cha. 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 In–Ho Cha. The network helps show where In–Ho Cha may publish in the future.

Co-authors

The 25 scholars most cited alongside In–Ho Cha, 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 In–Ho Cha Line = papers co-authored together In–Ho Cha links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 175 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep learning-based survival prediction of oral cancer patients
Hit paper breakdown →
2019219
2 2002146
3 2009144
4 2020123
5 2006118
6 2005116
7 200287
8 201273
9 200762
10 201461
11 200761
12 201859
13 200957
14 200149
15 200848
16 201145
17 200441
18 201341
19 199741
20 201440

About In–Ho Cha

In–Ho Cha is a scholar working on Otorhinolaryngology, Oral Surgery, Periodontics, Surgery and Orthopedics and Sports Medicine, having authored 175 papers that have together received 3.2k indexed citations. Recurring topics across this work include Head and Neck Cancer Studies (26 papers), Oral and Maxillofacial Pathology (23 papers), Reconstructive Surgery and Microvascular Techniques (18 papers), Bone health and treatments (16 papers), Bone Tumor Diagnosis and Treatments (14 papers), Head and Neck Surgical Oncology (13 papers), Cancer Diagnosis and Treatment (11 papers) and Oral health in cancer treatment (9 papers). The work is most often cited by research in Otorhinolaryngology (429 citations), Oral Surgery (647 citations), Health Informatics (63 citations), Periodontics (179 citations) and Orthopedics and Sports Medicine (243 citations). In–Ho Cha has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Hyung Jun Kim, Woong Nam, Dong Wook Kim, Ki‐Yeol Kim, Jin Kim, Jin‐Woo Kim, Jong In Yook, Sanghoon Lee, Myung-Rae Kim and Xianglan Zhang. Their work appears in journals such as International Journal of Oral and Maxillofacial Surgery, Head & Neck, Oral Oncology, Scientific Reports and Oral Diseases.

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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