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ChSatyaSavithChSatyaSavith
committed
Aaj thoda araam
1 parent 4d75568 commit 08bf0c6

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7 files changed

+552
-156
lines changed

7 files changed

+552
-156
lines changed

‎.vscode/settings.json

+5
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{
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"files.associations": {
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"iostream": "cpp"
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}
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}

‎6. Zigzag Conversion.cpp

+52
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class Solution {
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public:
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string convert(string s, int numRows)
4+
{
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vector<vector<char>> store;
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int n = numRows;
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if(n==1)
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{
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return s;
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}
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for(int i = 0;i<n;i++)
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{
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vector<char> temp;
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store.push_back(temp);
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}
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bool straight = true;
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int j = 0;
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for(int i = 0;i<s.size();i++)
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{
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if(j<n && straight)
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{
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store[j].push_back(s[i]);
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j+=1;
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if(j==n)
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{
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straight = false;
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j-=2;
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}
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}
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else
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{
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store[j].push_back(s[i]);
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j-=1;
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if(j<0)
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{
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straight = true;
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j+=2;
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}
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}
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}
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string toreturn = "";
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for(auto x:store)
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{
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for(auto y:x)
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{
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toreturn.push_back(y);
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}
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}
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return toreturn;
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}
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};

‎704. Binary Search.py

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class Solution(object):
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def search(self, nums, target):
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"""
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:type nums: List[int]
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:type target: int
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:rtype: int
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"""
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left = 0
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right = len(nums)-1
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while(left<=right):
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mid = (left+right)/2
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if(target==nums[mid]):
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return mid
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if(target<nums[mid]):
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right = mid - 1
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continue
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else:
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left = mid + 1
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continue
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return -1

‎keywords.csv

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Artificial intelligence
2+
deep learning
3+
machine learning
4+
osteoarthritis
5+
total hip arthroplasty
6+
hip dysplasia
7+
Activity recognition
8+
Machine learning
9+
Predictive modelling
10+
Performance evaluation
11+
Machine learning
12+
Gradient Boosting Machine
13+
Early stage prediction
14+
Diabetes mellitus
15+
Data mining
16+
Cardio-Vascular Diseases
17+
Classification
18+
Regression
19+
SVM
20+
Deep Learning
21+
Data Mining
22+
Machine Learning
23+
ANN
24+
Artificial Intelligence
25+
Artificial intelligence
26+
Heart disease detection system
27+
Machine learning
28+
Predictive analytics
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Random forest classifier algorithm
30+
Heart transplantation
31+
Primary graft failure
32+
Artificial neural network
33+
Prediction
34+
Multi-modality imaging
35+
Cardiac resynchronisation therapy
36+
Treatment response prediction
37+
Multi-view deep learning
38+
Machine learning
39+
Heart failure
40+
Risk factor analysis
41+
Feature importance
42+
Survival prediction
43+
Machine learning
44+
Bioinformatics
45+
MicroRNAs
46+
Correlations
47+
Link prediction
48+
Interpretable model
49+
Heart failure
50+
Machine learning
51+
SHAP value
52+
Covid-19
53+
Machine Learning
54+
Depression
55+
Artificial Intelligence
56+
Diabetes prediction
57+
Machine learning
58+
Flask
59+
Accuracy
60+
Random Forest
61+
Support Vector Machines
62+
Logistic regression
63+
Gradient boosting
64+
k-nearest neighbor
65+
echocardiography,
66+
electrocardiogram
67+
left ventricular diastolic
68+
dysfunction
69+
machine-learning
70+
myocardial
71+
relaxation
72+
SARS-COV-2
73+
Data Mining
74+
Deep Learning
75+
Extreme Gradient Boosting
76+
Machine Learning
77+
Heart failure
78+
Chronic-ischemic heart disease
79+
Machine learning
80+
Logistic regression
81+
Diagnostic
82+
Prediction
83+
Biosensor
84+
B-type natriuretic peptide
85+
Carbon nanotube
86+
Deep neural network
87+
Heart failure
88+
Machine learning
89+
Machine learning
90+
Medical diagnosis
91+
Heart disease
92+
Decision tree
93+
Combined dataset
94+
Heart sound
95+
Signal processing algorithms
96+
Machine learning algorithms
97+
Dimensional reduction algorithms
98+
Feature selection
99+
Gradient boosting classifier
100+
Heart failure
101+
Remote patient monitoring
102+
Machine learning
103+
Artificial intelligence
104+
Atrial fibrillation
105+
Heart rate sensor
106+
Machine learning
107+
Mobile health
108+
Smartwatch
109+
Photoplethysmography
110+
Wearable
111+
COVID-19
112+
deep learning
113+
multi-task learning
114+
convolutional neural networks
115+
chest radiography
116+
acute medically ill
117+
machine learning
118+
personalized medicine
119+
super learner
120+
venous
121+
thromboembolism
122+
Coronavirus disease 2019 (COVID-19)
123+
mortality
124+
machine learning
125+
prediction
126+
risk factors
127+
Artificial intelligence
128+
Machine learning
129+
Adverse drug reaction
130+
Drug toxicity
131+
Heart disease
132+
Machine learning
133+
Deep neural network
134+
K- means clustering
135+
Prediction
136+
Sensors
137+
SARS-CoV2
138+
COVID-19
139+
Coronavirus
140+
Deep learning
141+
Artificial intelligence
142+
Heart failure
143+
Readmission and mortality
144+
Survival analysis
145+
Machine learning
146+
Acute kidney injury
147+
Machine learning
148+
Artificial intelligence
149+
Logistic regression
150+
Cardiovascular disease
151+
Convolutional neural network
152+
Deep learning
153+
Left ventricular mass
154+
Machine learning
155+
Electrocardiogram
156+
Risk factor
157+
Diabetes mellitus
158+
Heart failure
159+
Machine learning
160+
deep learning
161+
diastolic dysfunction
162+
echocardiography
163+
heart failure with preserved ejection fraction
164+
Artificial intelligence
165+
BeatLogic
166+
Deep learning
167+
Electrocardiographic interpretation
168+
Preventice Solutions
169+
aortic regurgitation
170+
aortic stenosis
171+
artificial intelligence
172+
deep learning
173+
mitral regurgitation
174+
valvular heart disease
175+
Machine learning
176+
Heart diseases
177+
Feature selection
178+
Labeling
179+
Ensemble learning
180+
Validation metrics
181+
Heart Failure
182+
Mortality Prediction
183+
Electronic Health Records
184+
Feature Selection
185+
Multiple Kernel Learning
186+
Big data
187+
Electronic health data
188+
Heart failure
189+
Machine learning
190+
Readmission
191+
Coronary artery calcification(CAC)
192+
Machine learning(ML)
193+
Coronary artery calcification score (CACS)
194+
Coronary atherosclerotic heart disease(CHD)
195+
Coronary artery computed tomography
196+
angiography (CCTA)
197+
Unsupervised Machine learning
198+
Artificial intelligence
199+
Electronic health records
200+
Epidemiology
201+
Aging
202+
electrocardiogram
203+
electrophysiology
204+
convolutional neural network
205+
bidirectional LSTM
206+
deep learning
207+
Heart failure
208+
machine learning
209+
risk prediction
210+
readmissions
211+
administrative data
212+
artificial intelligence
213+
atrial fibrillation
214+
machine learning
215+
risk prediction
216+
Phonocardiogram
217+
Heart sounds
218+
Diastolic dysfunction detection
219+
Transfer learning
220+
Computer-aided diagnosis
221+
liver transplantation
222+
outcome prediction
223+
survival analysis
224+
Education
225+
Virtual Reality
226+
Eye Tracking
227+
Machine Learning
228+
Deep Learning
229+
Distraction Detection
230+
Phospholamban
231+
Deep learning
232+
Transfer learning
233+
ECG analysis
234+
Cardiomyopathy
235+
Genetic heart diseases

‎trial

38.8 KB
Binary file not shown.

‎trial.cpp

+37-25
Original file line numberDiff line numberDiff line change
@@ -1,36 +1,48 @@
1-
#include <stack>
1+
#include <vector>
22
#include <iostream>
33
using namespace std;
44

55
int main()
66
{
7-
string s = "()[]{}";
8-
stack<char> code;
7+
string s = "PAYPALISHIRING";
8+
vector<vector<char>> store(3);
9+
for(int i = 0;i<3;i++)
10+
{
11+
vector<char> temp;
12+
store.push_back(temp);
13+
}
14+
bool straight = true;
15+
int j = 0;
916
for(int i = 0;i<s.size();i++)
17+
{
18+
if(j<3 && straight)
1019
{
11-
switch(s[i])
20+
store[j].push_back(s[i]);
21+
j+=1;
22+
if(j==3)
1223
{
13-
case '(':
14-
code.push(')'); //Adding antimatter so i can neutralize when there occurs matter
15-
break;
16-
case '[':
17-
code.push(']'); //Adding antimatter so i can neutralize when there occurs matter
18-
break;
19-
case '{':
20-
code.push('}'); //Adding antimatter so i can neutralize when there occurs matter
21-
break;
22-
default:
23-
char top = code.top();
24-
cout<<top<<s[i]<<endl;
25-
code.pop();
26-
// if(top==s[i]) //Neutralizing open bracket with close bracket
27-
// {
28-
// code.pop();
29-
// }
30-
// else
31-
// {
32-
// return false;
33-
// }
24+
straight = false;
25+
j-=2;
3426
}
3527
}
28+
else
29+
{
30+
store[j].push_back(s[i]);
31+
j-=1;
32+
if(j<0)
33+
{
34+
straight = true;
35+
j+=2;
36+
}
37+
}
38+
}
39+
string toreturn = "";
40+
for(auto x: store)
41+
{
42+
for(auto y: x)
43+
{
44+
toreturn.push_back(y);
45+
}
46+
}
47+
cout<<toreturn<<endl;
3648
}

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