[C++] Solution, BFS approach. Beats 90%. Accurate code!!.
Code

# Code
```cpp []
class Solution {
public:
    bool findSafeWalk(vector<vector<int>>& grid, int health) {
        health -= grid[0][0];
        if (health <= 0) return false;

        const int N = grid.size();
        const int M = grid[0].size();

        auto in_range = [&](int row, int col) -> bool {
            return row >= 0 && row < N && col >= 0 && col < M;
        };

        std::vector< std::vector<int> > visited(N, std::vector<int>(M, -1));

        std::queue<Data> q;
        q.push(make_data(0, 0, health));

        int sz;
        int tmp_r, tmp_c;
        while ( q.empty() == false ) {
            sz = q.size();
            while ( sz-- ) {
                auto [r, c, h] = q.front();
                q.pop();

                // Optimization
                if (visited[r][c] > h) continue;

                if (r == N - 1 && c == M - 1) return true;

                for (const std::vector<int>& dir : dirs) {
                    tmp_r = r + dir[0];
                    tmp_c = c + dir[1];
                    if (in_range(tmp_r, tmp_c)) {
                        if ( h - grid[tmp_r][tmp_c] == 0 ) continue;

                        if (visited[tmp_r][tmp_c] == -1 || visited[tmp_r][tmp_c] < h - grid[tmp_r][tmp_c]) {
                            visited[tmp_r][tmp_c] =  h - grid[tmp_r][tmp_c];
                            q.push(make_data(tmp_r, tmp_c, visited[tmp_r][tmp_c]));
                        }
                    }
                }
            }
        }

        return false;
    }

private:
    std::vector<std::vector<int>> dirs{{1, 0}, {0, 1}, {-1, 0}, {0, -1}};

    struct Data
    {
        int row;
        int col;
        int health;
    };

    Data make_data(const int row, const int col, const int health) {  return Data{row, col, health}; }

};
```
['Breadth-First Search', 'C++']