Toshihiko Takada

5.2k citations
74 papers · 924 indexed · 1 hit paper · h-index 16

Toshihiko Takada

66 papers receiving 902 citations

Hit Papers

Risk of bias in studies on prediction models developed us...222202120262022202450100150200

Peers

Toshihiko Takada
Comparison fields: 5 of 131
  • Health Informatics 164
  • Family Practice 40
  • Health Information Management 54
  • Statistics, Probability and Uncertainty 50
  • Emergency Medicine 67
Replace Thomas D. Dobbs with:
Thomas D. Dobbs United Kingdom
Pauline Heus Netherlands
Patrícia Logullo United Kingdom
Chava L. Ramspek Netherlands
Katherine McAllister United Kingdom
Constanza L. Andaur Navarro Netherlands
Steven W J Nijman Netherlands
Erkin Ötleş United States
Bilal A. Mateen United Kingdom
Toshihiko Takada relative to Thomas D. Dobbs United Kingdom Thomas D. Dobbs's profile →
Citations per field
00.5×3.3×
Thomas D. Dobbs · 1×
Citations per year

Countries citing papers authored by Toshihiko Takada

Since Specialization
Citations

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

Fields of papers citing papers by Toshihiko Takada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20242
2 20239
3 202321
4 20230
5 20232
6 202258
7 202273
8 20218
9 20215
10
Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic reviewbreakdown →
2021222
11 20211
12 20214
13 202060
14 20201
15 202011
16 201914
17 20172
18 20130
19 20122
20
[Renal hemangiopericytoma discovered at a health screening: a case report].
20051

About Toshihiko Takada

Toshihiko Takada is a scholar working on Health Informatics, Family Practice and Applied Microbiology and Biotechnology, having authored 74 papers that have together received 924 indexed citations. Recurring topics across this work include Healthcare cost, quality, practices (7 papers), Clinical Reasoning and Diagnostic Skills (6 papers), Artificial Intelligence in Healthcare and Education (6 papers), Venous Thromboembolism Diagnosis and Management (5 papers), Machine Learning in Healthcare (5 papers), Sodium Intake and Health (4 papers), Orthopedic Infections and Treatments (4 papers) and Emergency and Acute Care Studies (4 papers). The work is most often cited by research in Health Informatics (164 citations), Family Practice (40 citations) and Health Information Management (54 citations). Toshihiko Takada has collaborated with scholars based in Japan, Netherlands and United Kingdom. Frequent co-authors include Steven W J Nijman, Lotty Hooft, Gary S. Collins, Constanza L. Andaur Navarro, Richard D Riley, Paula Dhiman, Johanna AAG Damen, Ram Bajpai, Jie Ma and Karel G.M. Moons. Their work appears in journals such as Journal of Clinical Epidemiology, BMJ Open, Cochrane Database of Systematic Reviews, Archives of Gerontology and Geriatrics and The American Journal of Emergency Medicine.

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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