File size: 1,404 Bytes
0d5a7ab
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>TrustAlert: News Anomaly Detection</title>
    <style>
        body {
            font-family: 'Segoe UI', sans-serif;
            line-height: 1.6;
            margin: 0;
            padding: 0;
            color: #333;
        }
        header {
            background-color: #2a4d69;
            color: white !important;
            padding: 20px;
            text-align: center;
        }
        section {
            padding: 20px;
            margin: 20px auto;
            color-scheme: light;
        }
        ul {
            padding-left: 20px;
        }
        body, p, ul, li, strong, code {
            color: #333;
        }
    </style>
</head>
<body>
    <header>
        <h1 style="color:white !important;">🛡️ TrustAlert: News Time Series Anomaly Detection</h1>
        <p style="color:white !important;">Detecting anomalies in disease-related news coverage using advanced time series analysis</p>
    </header>
    <section>
        <p>This tool analyzes temporal patterns in disease-related news coverage to identify potential outbreaks or unusual events. By detecting anomalies in the frequency of disease mentions, we can help public health officials spot emerging health concerns early.</p>
    </section>
</body>
</html>