﻿id	label	x	y	cluster	weight<Links>	weight<Total link strength>	weight<Occurrences>	score<Avg. pub. year>	score<Avg. citations>	score<Avg. norm. citations>
1	accuracy	-0.7433	0.2926	2	46	46	1	2022	1	0.8333
2	accuracy assessment	-0.5296	-0.2975	7	29	29	1	2020	35	2.4747
3	accurate prediction	0.5276	0.3079	3	19	19	1	2021	0	0
4	activation functions	0.4455	-0.044	4	20	20	1	2020	5	0.3535
5	aedes	-0.2548	0.2062	6	36	36	1	2020	25	1.7677
6	age distribution	-1.3209	-0.1316	8	18	18	1	2022	0	0
7	air temperature	-0.1937	-0.5294	1	38	38	1	2021	3	1.5
8	algorithm	-1.3514	-0.1387	8	18	18	1	2022	0	0
9	animal	-0.3022	0.3295	6	36	36	1	2020	25	1.7677
10	animals	-0.1885	0.2384	6	36	36	1	2020	25	1.7677
11	arima	-0.0936	-0.231	1	5	5	1	2022	1	0.8333
12	article	-0.6515	-0.1125	8	126	167	5	2021	12.8	1.3152
13	artificial neural network	-0.1193	-0.3903	1	41	43	2	2021.5	2	1.1667
14	atmospheric pressure	-0.3111	0.294	6	36	36	1	2020	25	1.7677
15	automated approach	1.2127	-0.4975	5	15	15	1	2020	10	0.7071
16	body temperature	-1.2753	-0.1588	8	18	18	1	2022	0	0
17	brain	0.39	0.6623	3	27	33	2	2020.5	1.5	0.75
18	brazil	-0.206	0.3422	6	36	36	1	2020	25	1.7677
19	calculation	-1.2988	-0.1424	8	18	18	1	2022	0	0
20	china	-0.5188	-0.3316	7	29	29	1	2020	35	2.4747
21	cities	-0.323	-0.4174	1	59	67	2	2020.5	19	1.9874
22	city	-0.2722	-0.1967	1	82	103	3	2020.3333	21	1.9141
23	climate	-0.397	-0.159	1	80	89	3	2021.6667	1.6667	1.0556
24	climate change	-0.6542	-0.0211	2	65	75	2	2021	18	1.654
25	climate data	0.3909	0.5723	3	17	17	1	2021	3	1.5
26	climate effect	-0.1982	-0.4605	1	38	38	1	2021	3	1.5
27	climate models	0.4856	0.4428	3	30	36	2	2021	1.5	0.75
28	climate variation	-0.0888	-0.583	1	38	38	1	2021	3	1.5
29	climatic conditions	0.4604	-0.1503	4	33	37	2	2019.5	8.5	0.6768
30	climatic variables	-0.1294	-0.4483	1	38	38	1	2021	3	1.5
31	cnn	0.4702	-0.0315	4	20	20	1	2020	5	0.3535
32	common cold	-1.3409	-0.1162	8	18	18	1	2022	0	0
33	communicable disease	-0.6973	0.2906	2	46	46	1	2022	1	0.8333
34	comparative study	-0.4928	-0.3019	7	29	29	1	2020	35	2.4747
35	computer language	-0.8691	0.2625	2	46	46	1	2022	1	0.8333
36	controlled study	-0.5176	0.2264	2	70	82	2	2021	13	1.3005
37	convolutional neural network	-0.8317	0.2015	2	46	46	1	2022	1	0.8333
38	correlation	-0.1763	-0.4913	1	38	38	1	2021	3	1.5
39	daily rainfall	1.0002	0.6803	9	14	14	1	2018	7	1
40	data analysis	-0.7687	0.1321	2	46	46	1	2022	1	0.8333
41	data processing	-0.7506	0.3424	2	46	46	1	2022	1	0.8333
42	decision trees	0.5717	0.328	3	19	19	1	2021	0	0
43	deep learning	0.3403	0.1975	5	160	211	10	2020.2	11.1	1.1263
44	dengue	-0.0788	0.1052	10	177	252	12	2021	6.5	1.0636
45	dengue detection	-1.2932	-0.1144	8	18	18	1	2022	0	0
46	dengue disease prediction	0.4417	-0.318	4	17	17	1	2019	12	1
47	dengue fever	-0.3204	-0.5877	7	62	71	3	2021	13	1.6027
48	dengue fevers	0.7924	0.5295	9	32	33	2	2019.5	3.5	0.5
49	dengue outbreak prediction	0.973	0.6932	9	14	14	1	2018	7	1
50	developing nations	0.4181	-0.2749	4	17	17	1	2019	12	1
51	diagnostic test accuracy study	-0.6892	0.2518	2	46	46	1	2022	1	0.8333
52	diarrhea	-0.7287	0.2047	2	46	46	1	2022	1	0.8333
53	discrete wavelength transform	0.0195	0.8651	10	4	4	1	2021	2	1
54	disease classification	1.0253	-0.5279	5	14	14	1	2020	23	1.6263
55	disease detection	1.2402	-0.44	5	15	15	1	2020	10	0.7071
56	disease incidence	-0.2182	-0.4925	1	38	38	1	2021	3	1.5
57	disease outbreaks	-0.3582	0.0055	6	54	65	2	2020	30	2.1212
58	disease spread	-0.1303	-0.5641	1	38	38	1	2021	3	1.5
59	disease trend prediction	0.3091	0.7558	3	16	16	1	2020	0	0
60	disease vector	-0.1246	-0.5203	1	38	38	1	2021	3	1.5
61	embedding technique	1.122	-0.5211	5	27	29	2	2020	16.5	1.1667
62	embeddings	1.2028	-0.4574	5	15	15	1	2020	10	0.7071
63	enhanced vegetation index	0.9573	0.678	9	14	14	1	2018	7	1
64	environmental conditions	-0.2795	-0.8186	7	4	4	1	2022	1	0.8333
65	environmental factor	-0.8078	0.1301	2	46	46	1	2022	1	0.8333
66	environmental temperature	-0.2189	0.2163	6	36	36	1	2020	25	1.7677
67	epidemic	-0.0887	-0.1431	1	97	123	4	2020.25	17	1.524
68	epidemic disease	0.4743	-0.0035	4	20	20	1	2020	5	0.3535
69	epidemiology	0.2448	0.0898	4	64	72	3	2020	12.3333	0.9226
70	evaporation	-0.7803	0.2625	2	46	46	1	2022	1	0.8333
71	fatality rates	0.4192	-0.3028	4	17	17	1	2019	12	1
72	feature selection	-0.2382	0.3603	6	36	36	1	2020	25	1.7677
73	forecast model	-0.4654	-0.272	7	29	29	1	2020	35	2.4747
74	forecasting	0.1802	0.2504	3	155	219	10	2020.3	8.9	0.9763
75	forecasting method	-0.563	-0.2798	7	29	29	1	2020	35	2.4747
76	gender	-1.3105	-0.1911	8	18	18	1	2022	0	0
77	geographical location	0.4026	0.0159	4	20	20	1	2020	5	0.3535
78	geospatial big data	0.475	-0.6026	10	4	4	1	2022	3	2.5
79	google earth engine	0.4866	-0.6047	10	4	4	1	2022	3	2.5
80	government websites	0.4415	-0.2888	4	17	17	1	2019	12	1
81	hazard	-0.7613	0.1787	2	46	46	1	2022	1	0.8333
82	health care	0.4366	-0.157	4	33	37	2	2019.5	8.5	0.6768
83	health care professionals	0.9812	-0.5541	5	14	14	1	2020	23	1.6263
84	health impact	-0.4977	-0.2587	7	29	29	1	2020	35	2.4747
85	health systems	0.4451	0.5725	3	17	17	1	2021	3	1.5
86	healthcare	0.4876	-0.2986	4	17	17	1	2019	12	1
87	healthcare industry	0.4175	-0.0121	4	20	20	1	2020	5	0.3535
88	human	-0.4193	-0.0517	1	112	149	4	2020.75	16	1.6439
89	humans	-0.3977	-0.0829	1	112	149	4	2020.75	16	1.6439
90	humidity	-0.4997	0.266	2	70	82	2	2021	13	1.3005
91	implementation science	-0.7595	0.2277	2	46	46	1	2022	1	0.8333
92	incidence	-0.4413	-0.078	1	112	149	4	2020.75	16	1.6439
93	infectious disease	0.4447	0.546	3	17	17	1	2021	3	1.5
94	influenza	-1.0602	0.0221	8	61	64	2	2022	0.5	0.4167
95	influenza detection	-1.3163	-0.1063	8	18	18	1	2022	0	0
96	information processing	-1.3061	-0.166	8	18	18	1	2022	0	0
97	infuenza	0.3936	-0.035	4	20	20	1	2020	5	0.3535
98	input factors	0.97	0.7136	9	14	14	1	2018	7	1
99	lasso regression	-0.2245	0.3024	6	36	36	1	2020	25	1.7677
100	learning approach	0.9896	-0.5736	5	14	14	1	2020	23	1.6263
101	learning models	0.5985	0.3328	3	19	19	1	2021	0	0
102	learning systems	0.949	0.7039	9	14	14	1	2018	7	1
103	local government	-0.5593	-0.3469	7	29	29	1	2020	35	2.4747
104	logistic regression	-0.2679	-0.8151	7	4	4	1	2022	1	0.8333
105	long short term memory	0.3667	0.7412	3	16	16	1	2020	0	0
106	long short term memory network	-0.7771	-0.0205	8	100	129	4	2021	15.25	1.2689
107	long short-term memory	0.1282	-0.0884	3	124	160	10	2020.7	6.7	0.7702
108	long-term dependencies	0.3648	0.6541	3	27	33	2	2020.5	1.5	0.75
109	lstm	0.4004	-0.1415	4	130	166	8	2020.5	7.625	1.166
110	machine learning	0.1953	0.1839	9	123	155	6	2020	15.1667	1.2837
111	major clinical study	-0.5698	-0.3151	7	29	29	1	2020	35	2.4747
112	malaria	-0.733	0.1453	2	46	46	1	2022	1	0.8333
113	malaysia	0.4196	0.582	3	17	17	1	2021	3	1.5
114	mathematical analysis	-1.3338	-0.1831	8	18	18	1	2022	0	0
115	mean absolute error	-0.7041	0.1718	2	46	46	1	2022	1	0.8333
116	mean square error	0.4953	0.1533	4	35	39	2	2020.5	2.5	0.1768
117	mean temperature	0.9692	0.6502	9	14	14	1	2018	7	1
118	measurement accuracy	-0.4939	-0.363	7	29	29	1	2020	35	2.4747
119	medical infrastructure	0.4881	-0.2705	4	17	17	1	2019	12	1
120	memory	-0.5306	-0.3685	7	29	29	1	2020	35	2.4747
121	memory-based learning	0.3647	0.7814	3	16	16	1	2020	0	0
122	meteorological phenomena	-0.79	0.3453	2	46	46	1	2022	1	0.8333
123	meteorology	0.4134	0.5539	3	17	17	1	2021	3	1.5
124	metropolitan area	-0.0619	-0.5171	1	38	38	1	2021	3	1.5
125	mortality rate	-0.7954	0.2169	2	46	46	1	2022	1	0.8333
126	mosquito	-0.1686	-0.5639	1	38	38	1	2021	3	1.5
127	mosquito-borne disease	0.9924	0.657	9	14	14	1	2018	7	1
128	multivariate analysis	-0.1788	0.2751	6	36	36	1	2020	25	1.7677
129	natural language processing	-0.8668	0.1839	2	46	46	1	2022	1	0.8333
130	"neural networks, computer"	-0.4532	-0.3067	7	29	29	1	2020	35	2.4747
131	number of iterations	0.444	-0.0116	4	20	20	1	2020	5	0.3535
132	on-line social networks	1.2171	-0.4403	5	15	15	1	2020	10	0.7071
133	overall response rate	-0.8412	0.1524	2	46	46	1	2022	1	0.8333
134	panama	-0.1552	-0.6032	1	38	38	1	2021	3	1.5
135	panama [central america]	-0.0631	-0.5543	1	38	38	1	2021	3	1.5
136	panama [panama (ntn)]	-0.0655	-0.4807	1	38	38	1	2021	3	1.5
137	panama [panama (prv)]	-0.158	-0.5272	1	38	38	1	2021	3	1.5
138	patient care	-1.328	-0.1556	8	18	18	1	2022	0	0
139	patient information	-1.3515	-0.164	8	18	18	1	2022	0	0
140	patient monitoring	0.4396	-0.2593	4	17	17	1	2019	12	1
141	performance measurements	1.2333	-0.4814	5	15	15	1	2020	10	0.7071
142	personal health informations	0.9847	-0.5325	5	14	14	1	2020	23	1.6263
143	personal information	1.0331	-0.5487	5	14	14	1	2020	23	1.6263
144	population statistics	0.4193	-0.0451	4	20	20	1	2020	5	0.3535
145	precipitation	-0.1657	-0.4454	1	38	38	1	2021	3	1.5
146	precipitation (climatology)	-0.1002	-0.4943	1	38	38	1	2021	3	1.5
147	prediction	-0.4789	-0.1379	1	78	84	2	2021.5	2	1.1667
148	prediction engines	0.938	0.684	9	14	14	1	2018	7	1
149	prediction methods	0.4287	0.0226	4	20	20	1	2020	5	0.3535
150	predictive value	-0.8549	0.2989	2	46	46	1	2022	1	0.8333
151	preventive action	0.5492	0.3608	3	19	19	1	2021	0	0
152	previous year	0.4651	-0.2568	4	17	17	1	2019	12	1
153	priority journal	-0.2773	0.3584	6	36	36	1	2020	25	1.7677
154	private hospitals	0.4646	-0.2852	4	17	17	1	2019	12	1
155	probability	-1.2759	-0.1333	8	18	18	1	2022	0	0
156	public health	-0.252	-0.0936	4	80	92	3	2020.3333	16	1.436
157	public sentiments	1.0089	-0.5602	5	14	14	1	2020	23	1.6263
158	python library	-0.7297	0.2544	2	46	46	1	2022	1	0.8333
159	rainy season	-0.8255	0.3265	2	46	46	1	2022	1	0.8333
160	random forest	-0.5368	0.2646	2	70	82	2	2021	13	1.3005
161	random forests	0.5464	0.3291	3	19	19	1	2021	0	0
162	recurrent neural networks	1.006	-0.5408	5	14	14	1	2020	23	1.6263
163	recurrent neural networks (rnns)	-0.2767	-0.8071	7	4	4	1	2022	1	0.8333
164	regression analysis	-0.2691	0.285	6	36	36	1	2020	25	1.7677
165	relative humidity	-0.2297	-0.5288	1	38	38	1	2021	3	1.5
166	research approach	1.2329	-0.5063	5	15	15	1	2020	10	0.7071
167	retrospective study	-0.6897	0.2126	2	46	46	1	2022	1	0.8333
168	rio de janeiro (state)	-0.3057	0.2577	6	36	36	1	2020	25	1.7677
169	risk forecasting	0.4787	-0.6136	10	4	4	1	2022	3	2.5
170	risk perception	0.9483	0.6591	9	14	14	1	2018	7	1
171	rnn	0.4589	-0.4663	5	68	69	3	2020	12.6667	1.3754
172	root mean square errors	0.3868	-0.008	4	20	20	1	2020	5	0.3535
173	root mean squared error	-0.7156	0.3257	2	46	46	1	2022	1	0.8333
174	rural areas	0.4668	-0.3153	4	17	17	1	2019	12	1
175	safety precautions	0.455	0.0178	4	20	20	1	2020	5	0.3535
176	sarima	-0.1918	-0.5934	1	38	38	1	2021	3	1.5
177	sarimax	-0.2151	-0.565	1	38	38	1	2021	3	1.5
178	scale up	-0.8001	0.1719	2	46	46	1	2022	1	0.8333
179	season	-0.5212	0.3041	2	70	82	2	2021	13	1.3005
180	seasons	-0.2215	0.2642	6	36	36	1	2020	25	1.7677
181	short term	0.3414	0.7883	3	16	16	1	2020	0	0
182	short term memory	0.3785	0.762	3	16	16	1	2020	0	0
183	social media	1.2286	-0.4616	5	15	15	1	2020	10	0.7071
184	social media platforms	1.0309	-0.57	5	14	14	1	2020	23	1.6263
185	social networking (online)	1.1158	-0.5017	5	27	29	2	2020	16.5	1.1667
186	solar radiation	-0.817	0.282	2	46	46	1	2022	1	0.8333
187	spatial analysis	1.2531	-0.4959	5	15	15	1	2020	10	0.7071
188	spatio-temporal analysis	-0.2901	0.2239	6	36	36	1	2020	25	1.7677
189	spatiotemporal analysis	-0.2578	0.3217	6	36	36	1	2020	25	1.7677
190	standard evaluations	1.2598	-0.4752	5	15	15	1	2020	10	0.7071
191	state-of-the-art approach	1.2051	-0.478	5	15	15	1	2020	10	0.7071
192	state-of-the-art techniques	1.004	-0.5185	5	14	14	1	2020	23	1.6263
193	support vector regression	0.4227	0.5274	3	17	17	1	2021	3	1.5
194	support vector regression (svr)	0.3943	0.528	3	17	17	1	2021	3	1.5
195	temperature	-0.0971	-0.5419	1	38	38	1	2021	3	1.5
196	temporal relationships	0.3194	0.7342	3	16	16	1	2020	0	0
197	text mining	-1.2858	-0.1815	8	18	18	1	2022	0	0
198	text processing	1.0113	-0.5822	5	14	14	1	2020	23	1.6263
199	the philippines	0.028	0.8567	10	4	4	1	2021	2	1
200	three models	0.9925	0.7017	9	14	14	1	2018	7	1
201	time series	0.2648	0.2618	3	75	90	4	2020.75	1.5	0.75
202	time series analysis	0.0388	-0.0021	1	79	93	3	2020.6667	9.3333	1.0892
203	time series clustering	0.5856	0.3016	3	19	19	1	2021	0	0
204	time series forecasting	0.22	0.3886	3	60	72	3	2020.6667	9.3333	1.0892
205	time-series data	0.3436	0.7313	3	16	16	1	2020	0	0
206	time-series regression	0.3423	0.7592	3	16	16	1	2020	0	0
207	times series	0.5222	0.3415	3	19	19	1	2021	0	0
208	times series forecasting	0.5562	0.2952	3	19	19	1	2021	0	0
209	traditional approaches	0.5787	0.3589	3	19	19	1	2021	0	0
210	training	-0.8289	0.2446	2	46	46	1	2022	1	0.8333
211	transfer learning	-0.5322	-0.2574	7	29	29	1	2020	35	2.4747
212	transfer of learning	-0.4704	-0.3379	7	29	29	1	2020	35	2.4747
213	trend prediction	0.3194	0.7776	3	16	16	1	2020	0	0
214	tropical meteorology	-0.1195	-0.6016	1	38	38	1	2021	3	1.5
215	tropical region	-0.1403	-0.4832	1	38	38	1	2021	3	1.5
216	univariate long-short term memory network	0.031	0.8681	10	4	4	1	2021	2	1
217	urban area	-0.0942	-0.4548	1	38	38	1	2021	3	1.5
218	viet nam	-0.7809	0.3054	2	46	46	1	2022	1	0.8333
219	vietnam	-0.8725	0.2245	2	46	46	1	2022	1	0.8333
220	virology	-0.1834	0.3121	6	36	36	1	2020	25	1.7677
221	virus transmission	-0.2562	0.2488	6	36	36	1	2020	25	1.7677
222	weather	-0.1861	0.0952	4	63	66	2	2021	3	0.5934
223	weather data	0.3769	0.549	3	17	17	1	2021	3	1.5
224	wind	0.9785	0.672	9	14	14	1	2018	7	1
225	word2vec	1.255	-0.4555	5	15	15	1	2020	10	0.7071
